DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Amendments
Claims 1-6, 8-12, 15-18, and 21-25 are currently pending in this case and have been examined and addressed below. This communication is a Final Rejection in response to the Amendment to the Claims and Remarks filed on 09/11/2025.
Claims 1, 8, and 15 are amended claims.
Claims 2-6, 9-12, 16-18, and 21-25 are previously presented.
Claims 7, 13-14, and 19-20 have been cancelled and will not be considered at this time.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4, 6, 8-11, 15-18, and 23-25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dugan (US 20230113555 A1) in view of Vaccaro (US 11328806 B2) in view of Sampath (US 20180174680 A1) in view of Stoppelkamp (Identification of Predictive Early Biomarkers for Sterile-SIRS after Cardiovascular Surgery (2015)) in view of Shelton (US 20190206563 A1) in view of Nawana (US 20190216452 A1) in view of Harris (US 20190206003 A1).
As per Claim 1, Dugan teaches A computer system for outcome tracking of a patient, comprising:
a processor; ([Para. 0025] a processor.)
and a memory coupled to the processor, the memory storing instructions, that when executed by the processor, cause the computer system to: ([Para. 0072] a memory unit.)
generate an event trigger for the patient, the event trigger corresponds to a condition being met when the patient is performing a post-surgery activity related to the recovery of the patient; ([Para. 0029] recorded time series of orientation risk values with the recorded time series of activity risk values to generate a continuous time series of risk values. A cumulative risk may be calculated on a subset of the continuous time series of risk values by calculating a moving average for a subset of the continuous time series of risk values. Thereafter, the processor may be configured to compare the cumulative risk to a cumulative risk threshold value and output a warning when the cumulative risk crosses the cumulative risk threshold value. [Para. 0022] the system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters (biomarker data from sensor(s)). [Para. 0073] informs the user when a risk value exceeds the threshold value for a physiological parameter. [Para. 0162] analyzes a predetermined number of the most recently recorded physiological parameters to determine if one or more of the detected parameters is abnormal as determined over a set period of time. When at least one of the physiological parameters is determined to be abnormal, an alert is generated.)
based on the values of the patient biomarker being over or under the post-surgery threshold values when the patient is performing the post-surgery activity, determine whether the condition is met; ([Para. 0022] the physiological parameters recorded by the sensors can include abdominal/body orientation, snoring, blood oxygen, blood pressure, location of center of gravity, activities like running, walking, driving, sleeping, body heat, altitude tracking, pressure readings, temperature readings, and/or user pedometer readings, breathing during sleep, respiration characteristics, tension, temperature (measured at any variety of locations on or in the body), and/or hemodynamic flow restriction. The system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters. [Para. 0025] compare the first cumulative risk value to a first threshold and output a warning when the first cumulative risk value crosses the first threshold. [Para. 0073]The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter.)
based on the condition being met, trigger the event trigger; ([Para. 0073]The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter.)
generate a notification alert corresponding to the event trigger; ([Para. 0025] teaches compare the first cumulative risk value to a first threshold and output a warning when the first cumulative risk value crosses the first threshold.)
Dugan does explicitly disclose, however Vaccaro discloses
wherein during a duration of a recovery of the patient from a surgical procedure, ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
determine post-surgery complications associated with the recovery of the patient from the surgical procedure; ([Col. 15, Lined 10-17] The collection of the data and storage in the patient's EMR further permits the physician or medical professional to provide a remote watch-dog function, detect complications, detect noncompliance with prescribed therapies, detect other pathologies and otherwise maintain access to patient progress or regression without requiring the physical presence of the patient with the physician or physical therapist.)
receive an indication from the patient sensor system if measured values of the patient biomarker are over or under the post-surgery threshold values associated with the patient biomarker when the patient is performing the post-surgery activity; ([Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data, and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 32-44] 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in (i.e. threshold) . However, pain reported by the patient remains high, and is, in fact, in the top 15% (i.e. over the threshold values). This condition results in sending prompts (i.e. indication) to both the patient and the physician. The patient is prompted via SMS or a mobile app (i.e. patient sensor system) to reach out to their medical provider. The medical provider is prompted via SMS or a physician user interface to review the patient's chart, and, if necessary, have a member of the staff contact the patient.)
display the real time data analytics, wherein the real time data analytics are displayed via a graph showing patient recovery data during the recovery threshold window; ([Col. 1, Lines 25-31] the comparator 116 of the processor 114 temporally compares the patient's actual post-procedural state to the predictive model of the patient's post-procedural state and outputs the results of the comparison., The comparison is shown as another line on the temporal trendline graphs of FIGS. 4A and 4B. See, the dot-dash lines in FIGS. 5A and 5B. [Col. 3, Lines 37-44] The comparator 116 of the processor 114 temporally compares the post-procedural walking parameters, including steps taken, to the temporal trendline of post-procedural walking parameters, including steps taken. The comparator 116 of the processor also temporally compares the post-procedural pain level to the temporal trendline of post-procedural pain level. The comparator 116 of the processor 114 further outputs the results of the comparison. [Col. 6, Lines 32-37, 40-43] In the example of FIGS. 5A and 5B, 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in. However, pain reported by the patient remains high, and is, in fact, in the top 15%. The medical provider is prompted via SMS or a physician user interface to review the patient's chart, and, if necessary, have a member of the staff contact the patient. [Col. 13, Lines 39-46] Referring to FIGS. 9A-9D, taken together, the preferred data collection tools 50 are able to acquire consistent walking and movement information from the patient, particularly post-operative walking or movement activity. FIGS. 9A-9D, taken together, provide examples of graphic displays of information the data collection tools 50 may acquire and transmit to the central server 40 for storage in the patient's EMR.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
Dugan/ Vaccaro do not explicitly disclose, however Sampath discloses
send the post-surgery threshold values associated with the patient biomarker to a patient sensor system; ([Para. 0200] A clinician may also use an input device to alter patient monitoring settings such as, for example, options for calculating physiological parameter values from raw data, alarm types, physiological parameter alarm limits (e.g. post-surgery thresholds), etc. Examiner interprets altering the physiological parameter alarm limits to be indicative of sending threshold values.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and incorporate determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, with the motivation of acquiring physiological information from patients, analyzing the physiological information, and communicating the physiological information to clinicians and other systems or devices (Sampath Para. 0002).
Dugan/ Vaccaro/ Sampath do not explicitly teach, however Stoppelkamp teaches
determine post-surgery threshold values associated with a patient biomarker based on the determined post-surgery complications, wherein the post-surgery threshold values are outside of a normal threshold value range; ([Pg. 2 Introduction] patients undergoing cardiovascular surgery often are elderly and represent with comorbidities and a weakened general condition. Those patients are therefore especially at risk of complications such as systemic inflammatory response syndrome (SIRS). This generic term encompasses sterile inflammation as well as sepsis (that is SIRS with confirmed bacteremia) and is defined by meeting two or more of the following criteria: 1) a temperature of above 38°C or below 36°C, 2) a heart rate over 90 beats/min, 3) a respiratory rate above 20 breaths/min or decreased paCO2 below 32 mmHg, 4) white blood cell count of over 12000 cells/mm3 or under 4000 cells/mm3 or more than 10% immature neutrophils)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, and incorporate identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, with the motivation of predicting the development of Systemic inflammatory response syndrome (SIRS) available for clinical decision in the early post-operative period or at early hours in the ICU in order to timely counteract the dysregulation of the immune system (Stoppelkamp Pg. 3 Introduction).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp do not explicitly teach, however Shelton teaches
control, via a plurality of first control signals, a plurality of surgical devices; ([Para. 0313] the computer-implemented interactive surgical system is configured to monitor and analyze data related to the operation of various surgical systems that include surgical hubs, surgical instruments (i.e. surgical devices), robotic devices and operating theaters or healthcare facilities. Surgical hubs 7006 that are coupled to the cloud 7004 can be considered the client side of the cloud computing system (i.e., cloud-based analytics system). Surgical instruments 7012 are paired with the surgical hubs 7006 for control and implementation of various surgical procedures or operations.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, and incorporate methods for adaptive control of surgical network control and interaction as taught by Shelton, with the motivation of helping interconnect medical systems and facilities to better improve patient practices (Shelton Para. 0013).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton do not explicitly teach, however Nawana teaches
generate, via the patient sensor system, biomarker data and physical state data of the patient; ([Para. 0031] Receiving the information regarding the at least one of the plurality of patient-specific factors can include receiving data from a plurality of sensors. [Para. 0032] The diagnosis and treatment module receiving the information regarding the plurality of symptoms (i.e. physical state) can include receiving data from a plurality of sensors. [Para. 0033] The monitoring can include at least one of vital signs (i.e. biomarker) of the patient.)
generate, via an environmental sensing system, environmental data associated with the surgical procedure; ([Para. 0034] The operation module can provide the electronic feedback on a display, and the operation module can provide additional electronic information regarding the actual performance of the selected invasive treatment on the display including any one or more of a fluoroscopic image of the patient, vital signs of the patient, neural monitoring outputs, surgical techniques videos, camera feeds from outside a room where the selected invasive treatment is being performed, power usage of instruments, and controls for any one or more devices that gather the additional electronic information and provide the additional electronic information to the operation module.)
infer, via a situational awareness system, surgical procedural outcome data based on the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0120] The system 10 can allow paths of an individual's medical treatment through all or part of the continuum 22 to be compared and consolidated then applied to patients with similar symptoms to diagnose and choose the treatment that previously produced a best outcome for similarly situated patients. The outcome can include technical, anatomic, functional, and patient reported parameters.)
output, to a facility analytics system within a recovery threshold window, the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0296] The surgery feedback module 238 can be configured to generate one or more post-op reports summarizing the surgery performed. A post-op report generated for a medical practitioner such as the performing surgeon or the patient's PCP can include medically precise information regarding the surgery and/or the patient, such as the type of surgery performed (i.e. environmental data), the medical devices implanted in the patient, date of the surgery, the medications administered to the patient, projected success rate of the surgery based on historic success rates of the surgery and the patient's particular surgery, etc. [Para. 0321] The patient monitoring module 244 can be configured to provide a user with information regarding a patient's post-op treatment plan, such as by displaying post-op treatment plan information on a device in communication with the system 10. Non-limiting examples of post-op treatment plan information that can be displayed on the device include reminders for upcoming post-op appointments (e.g., physical therapy appointments), reminders of days/times to take medication, percentage of overall compliance with the post-op treatment plan, reminders to upload data (e.g., video of exercise, blood pressure and/or other vital sign reading (i.e. biomarker), etc.), current list of symptoms and/or pain levels, (i.e. physical state), etc.) (e.g., the data being uploaded by the patient post-op and within a recovery threshold window)
receive, from the facility analytics system, real time data analytics associated with the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0034] The operation module can provide the electronic feedback on a display, and the operation module can provide additional electronic information regarding the actual performance of the selected invasive treatment on the display including any one or more of a fluoroscopic image of the patient, vital signs of the patient, neural monitoring outputs, surgical techniques videos, camera feeds from outside a room where the selected invasive treatment is being performed, power usage of instruments, and controls for any one or more devices that gather the additional electronic information and provide the additional electronic information to the operation module.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, adaptive control of surgical network control and interaction as taught by Shelton, and incorporate an operating room analysis module as taught by Nawana, with the motivation of providing improved systems and methods for surgical and interventional planning, support, post-operative follow-up, and functional recovery tracking (Nawana Para. 0019).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp/Shelton/Nawana do not explicitly teach, however Harris teaches
receive an updated control program from the facility analytics system based on the real time data analytics; ([Para. 0298] The surgical hub 9000 can sense or receive perioperative data from the modular devices 9050 and then associate the received perioperative data with surgical procedural outcome data. The perioperative data indicates how the modular devices 9050 were controlled during the course of a surgical procedure. The procedural outcome data includes data associated with a result from the surgical procedure (or a step thereof), which can include whether the surgical procedure (or a step thereof) had a positive or negative outcome. [Para. 0299] The surgical hub 9000 can transmit the associated modular device 9050 data and outcome data to the analytics system 9100 for processing thereon. By transmitting both the perioperative data indicating how the modular devices 9050 are controlled and the procedural outcome data, the analytics system 9100 can correlate the different manners of controlling the modular devices 9050 with surgical outcomes for the particular procedure type)
and update the control of the plurality of surgical devices, via a plurality of second control signals, based on the updated control program and the inferred surgical procedural outcome data. ([Para. 0299] Based on this paired data, the analytics system 9100 can then learn optimal or preferred operating parameters for the various types of modular devices 9050, generate adjustments to the control programs of the modular devices 9050 in the field, and then transmit (or “push”) updates to the modular devices' 9050 control programs.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, adaptive control of surgical network control and interaction as taught by Shelton, an surgical and interventional planning as taught by Nawana, and incorporate adaptive control program updates for surgical devices as taught by Harris, with the motivation of helping interconnect medical systems and facilities better to ensure patient safety (Harris Para. 0003.)
As per Claim 2, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Dugan further teaches wherein the values of the patient biomarker being over or under the post-surgery threshold values are biomarker levels outside of an expected operating ([Para. 0073] the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter. The feedback system where the feedback system informs the user when a physiological parameter is inside the minimum and maximum threshold values. The feedback system where the feedback system informs the user when the time average of a physiological parameter is exceeds the threshold values.)
Dugan does not explicitly disclose, however Vaccaro discloses
when the patient is performing the post-surgery activity. ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters. [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data (i.e. post-surgery activity), and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters, users receive feedback on post-procedural progress. [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 3, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/Shelton/Nawana/ Harris teach the computer system of claim 1, Dugan further teaches wherein the condition is met if the values of the patient biomarker are determined to be over or under the post-surgery threshold values for a predetermined period of time ([Para. 0073] The processing system where the processing system identifies risk values associated with one or more physiological parameters. The processing system where the physiological parameters are selected from the group including: abdominal/body orientation, snoring, blood oxygen, blood pressure, location of center of gravity, physical activity, body heat, altitude tracking, pressure, temperature, respiration, respiration during sleep, tension, and hemodynamic flow. The processing system where the processing system determines risk values by creating a moving average of the physiological parameter data and comparing it to a threshold. The processing system where the moving average calculated over any of a variety of time spans. The processing system where there is a minimum and maximum threshold limitation. The processing system where the processor is coupled with manual inputs. The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter. Examiner interprets the function of when the feedback system informs the user to be indicative of the condition being met.)
Dugan does not explicitly disclose, however Vaccaro discloses
during the duration of the patient's recovery. ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters. [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data (i.e. post-surgery activity), and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters, users receive feedback on post-procedural progress. [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 4, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Dugan further teaches wherein the processor is further configured to send the notification alert to a healthcare facility, and wherein the notification alert is accessed by multiple different caregivers to synchronize their handling of the patient within the healthcare facility. ([Para. 0087] an alert from the wearable device to one or more caregivers of the individual upon determining that the physical orientation has not changed by the prescribed amount within a second time interval following the first- time interval. [Para. 0088] the method of Example 7, wherein issuing the alert to the one or more caregivers comprises issuing an alert to a caregiver monitoring station. [Para. 0529] monitoring the body position within the healthcare facility 820 and issuing a first alert 830 from the wearable device 10 through a first wireless communication link of the healthcare facility. For example, the first alert 830 may be a wireless transmission sent from the device to a monitoring station 840 over the facility's wide area network, a personal area network, a Bluetooth communication and the like.)
As per Claim 6, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Vaccaro further teaches wherein the values of the patient biomarker are heart rate values and the post-surgery activity is recovering after exercise. ([Col. 13, Lines 5-10] Referring to FIG. 7B, the data collection tools 50 may comprise an epidermal electronics data acquisition tool 50a. The epidermal electronics data acquisition tool 50a is preferably attachable to the patient's skin, similar to a temporary tattoo, is preferably disposable and has the ability to track heart rate. [Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters. [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data (i.e. post-surgery activity), and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters, users receive feedback on post-procedural progress. [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.))
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 8, Dugan teaches a computer-implemented method for providing outcome tracking of a patient, comprising:
generating an event trigger for the patient, the event trigger corresponds to a condition being met; ([Para. 0029] recorded time series of orientation risk values with the recorded time series of activity risk values to generate a continuous time series of risk values. A cumulative risk may be calculated on a subset of the continuous time series of risk values by calculating a moving average for a subset of the continuous time series of risk values. Thereafter, the processor may be configured to compare the cumulative risk to a cumulative risk threshold value and output a warning when the cumulative risk crosses the cumulative risk threshold value. [Para. 0022] the system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters (biomarker data from sensor(s)). [Para. 0073] informs the user when a risk value exceeds the threshold value for a physiological parameter. [Para. 0162] analyzes a predetermined number of the most recently recorded physiological parameters to determine if one or more of the detected parameters is abnormal as determined over a set period of time. When at least one of the physiological parameters is determined to be abnormal, an alert is generated.)
and based on the values of the patient biomarker being over or under the post-surgery threshold values while the patient is performing a post-surgery activity, determine whether the condition is met; ([Para. 0022] the physiological parameters recorded by the sensors can include abdominal/body orientation, snoring, blood oxygen, blood pressure, location of center of gravity, activities like running, walking, driving, sleeping, body heat, altitude tracking, pressure readings, temperature readings, and/or user pedometer readings, breathing during sleep, respiration characteristics, tension, temperature (measured at any variety of locations on or in the body), and/or hemodynamic flow restriction. The system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters. [Para. 0025] compare the first cumulative risk value to a first threshold and output a warning when the first cumulative risk value crosses the first threshold. [Para. 0073]The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter.)
based on the condition being met, triggering the event trigger; ([Para. 0073]The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter.)
generating a notification alert corresponding to the event trigger; ([Para. 0025] teaches compare the first cumulative risk value to a first threshold and output a warning when the first cumulative risk value crosses the first threshold.)
Dugan does not explicitly disclose, however Vaccaro discloses
wherein during a duration of a recovery of the patient from a surgical procedure ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
when the patient is performing a post-surgery activity related to the recovery of the patient ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data, and a mobile device (e.g., smartphone) including an application configured to receive data from the device.[Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters , users receive feedback on post-procedural progress.)
determining post-surgery complications associated with the recovery of the patient from the surgical procedure; ([Col. 15, Lined 10-17] The collection of the data and storage in the patient's EMR further permits the physician or medical professional to provide a remote watch-dog function, detect complications, detect noncompliance with prescribed therapies, detect other pathologies and otherwise maintain access to patient progress or regression without requiring the physical presence of the patient with the physician or physical therapist.)
receiving an indication from the patient sensor system if measured values of the patient biomarker are over or under the post-surgery threshold values associated with the patient biomarker when the patient is performing a post-surgery activity; ; ([Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data, and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 32-44] 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in (i.e. threshold) . However, pain reported by the patient remains high, and is, in fact, in the top 15% (i.e. over the threshold values). This condition results in sending prompts (i.e. indication) to both the patient and the physician. The patient is prompted via SMS or a mobile app (i.e. patient sensor system) to reach out to their medical provider. The medical provider is prompted via SMS or a physician user interface to review the patient's chart, and, if necessary, have a member of the staff contact the patient.)
displaying the real time data analytics, wherein the real time data analytics are displayed via a graph showing patient recovery data during the recovery threshold window; ([Col. 1, Lines 25-31] the comparator 116 of the processor 114 temporally compares the patient's actual post-procedural state to the predictive model of the patient's post-procedural state and outputs the results of the comparison. In one preferred embodiment, the comparison is shown as another line on the temporal trendline graphs of FIGS. 4A and 4B. See, the dot-dash lines in FIGS. 5A and 5B. [Col. 6, Lines 32-37] In the example of FIGS. 5A and 5B, 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in. However, pain reported by the patient remains high, and is, in fact, in the top 15%.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
Dugan/ Vaccaro do not explicitly disclose, however Sampath discloses
sending the post-surgery threshold values associated with values of a the patient biomarker to a patient sensor system; ([Para. 0200] A clinician may also use an input device to alter patient monitoring settings such as, for example, options for calculating physiological parameter values from raw data, alarm types, physiological parameter alarm limits (e.g. post-surgery thresholds), etc. Examiner interprets altering the physiological parameter alarm limits to be indicative of sending threshold values.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and incorporate determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, with the motivation of acquiring physiological information from patients, analyzing the physiological information, and communicating the physiological information to clinicians and other systems or devices (Sampath Para. 0002).
Dugan/ Vaccaro/ Sampath do not explicitly teach, however Stoppelkamp teaches
determining post-surgery threshold values associated with a patient biomarker based on the determined post-surgery complications, wherein the post-surgery threshold values are outside of a normal threshold value range; ([Pg. 2 Introduction] patients undergoing cardiovascular surgery often are elderly and represent with comorbidities and a weakened general condition. Those patients are therefore especially at risk of complications such as systemic inflammatory response syndrome (SIRS). This generic term encompasses sterile inflammation as well as sepsis (that is SIRS with confirmed bacteremia) and is defined by meeting two or more of the following criteria: 1) a temperature of above 38°C or below 36°C, 2) a heart rate over 90 beats/min, 3) a respiratory rate above 20 breaths/min or decreased paCO2 below 32 mmHg, 4) white blood cell count of over 12000 cells/mm3 or under 4000 cells/mm3 or more than 10% immature neutrophils)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, and incorporate identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, with the motivation of predicting the development of Systemic inflammatory response syndrome (SIRS) available for clinical decision in the early post-operative period or at early hours in the ICU in order to timely counteract the dysregulation of the immune system (Stoppelkamp Pg. 3 Introduction).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp do not explicitly teach, however Shelton teaches
control, via a plurality of first control signals, a plurality of surgical devices; ([Para. 0313] the computer-implemented interactive surgical system is configured to monitor and analyze data related to the operation of various surgical systems that include surgical hubs, surgical instruments (i.e. surgical devices), robotic devices and operating theaters or healthcare facilities. Surgical hubs 7006 that are coupled to the cloud 7004 can be considered the client side of the cloud computing system (i.e., cloud-based analytics system). Surgical instruments 7012 are paired with the surgical hubs 7006 for control and implementation of various surgical procedures or operations.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, and incorporate methods for adaptive control of surgical network control and interaction as taught by Shelton, with the motivation of helping interconnect medical systems and facilities to better improve patient practices (Shelton Para. 0013).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton do not explicitly teach, however Nawana teaches
generating, via the patient sensor system, biomarker data and physical state data of the patient; ([Para. 0031] Receiving the information regarding the at least one of the plurality of patient-specific factors can include receiving data from a plurality of sensors. [Para. 0032] The diagnosis and treatment module receiving the information regarding the plurality of symptoms (i.e. physical state) can include receiving data from a plurality of sensors. [Para. 0033] The monitoring can include at least one of vital signs (i.e. biomarker) of the patient.)
generating, via an environmental sensing system, environmental data associated with the surgical procedure; ([Para. 0034] The operation module can provide the electronic feedback on a display, and the operation module can provide additional electronic information regarding the actual performance of the selected invasive treatment on the display including any one or more of a fluoroscopic image of the patient, vital signs of the patient, neural monitoring outputs, surgical techniques videos, camera feeds from outside a room where the selected invasive treatment is being performed, power usage of instruments, and controls for any one or more devices that gather the additional electronic information and provide the additional electronic information to the operation module.)
inferring, via a situational awareness system, surgical procedural outcome data based on the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0120] The system 10 can allow paths of an individual's medical treatment through all or part of the continuum 22 to be compared and consolidated then applied to patients with similar symptoms to diagnose and choose the treatment that previously produced a best outcome for similarly situated patients. The outcome can include technical, anatomic, functional, and patient reported parameters.)
outputting, to a facility analytics system within a recovery threshold window, the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0296] The surgery feedback module 238 can be configured to generate one or more post-op reports summarizing the surgery performed. A post-op report generated for a medical practitioner such as the performing surgeon or the patient's PCP can include medically precise information regarding the surgery and/or the patient, such as the type of surgery performed (i.e. environmental data), the medical devices implanted in the patient, date of the surgery, the medications administered to the patient, projected success rate of the surgery based on historic success rates of the surgery and the patient's particular surgery (i.e. physical state), etc. [Para. 0321] The patient monitoring module 244 can be configured to provide a user with information regarding a patient's post-op treatment plan, such as by displaying post-op treatment plan information on a device in communication with the system 10. Non-limiting examples of post-op treatment plan information that can be displayed on the device include reminders for upcoming post-op appointments (e.g., physical therapy appointments), reminders of days/times to take medication, percentage of overall compliance with the post-op treatment plan, reminders to upload data (e.g., video of exercise, blood pressure and/or other vital sign reading (i.e. biomarker), etc.), current list of symptoms and/or pain levels, etc.)
receiving, from the facility analytics system, real time data analytics associated with the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0034] The operation module can provide the electronic feedback on a display, and the operation module can provide additional electronic information regarding the actual performance of the selected invasive treatment on the display including any one or more of a fluoroscopic image of the patient, vital signs of the patient, neural monitoring outputs, surgical techniques videos, camera feeds from outside a room where the selected invasive treatment is being performed, power usage of instruments, and controls for any one or more devices that gather the additional electronic information and provide the additional electronic information to the operation module.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, adaptive control of surgical network control and interaction as taught by Shelton, and incorporate an surgical and interventional planning as taught by Nawana, with the motivation of providing improved systems and methods for surgical and interventional planning, support, post-operative follow-up, and functional recovery tracking (Nawana Para. 0019).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana do not explicitly teach, however Harris teaches
receiving an updated control program from the facility analytics system based on the real time data analytics; ([Para. 0298] The surgical hub 9000 can sense or receive perioperative data from the modular devices 9050 and then associate the received perioperative data with surgical procedural outcome data. The perioperative data indicates how the modular devices 9050 were controlled during the course of a surgical procedure. The procedural outcome data includes data associated with a result from the surgical procedure (or a step thereof), which can include whether the surgical procedure (or a step thereof) had a positive or negative outcome. [Para. 0299] The surgical hub 9000 can transmit the associated modular device 9050 data and outcome data to the analytics system 9100 for processing thereon. By transmitting both the perioperative data indicating how the modular devices 9050 are controlled and the procedural outcome data, the analytics system 9100 can correlate the different manners of controlling the modular devices 9050 with surgical outcomes for the particular procedure type. )
and updating the control of the plurality of surgical devices, via a plurality of second control signals, based on the updated control program and the inferred surgical procedural outcome data. ([Para. 0299] Based on this paired data, the analytics system 9100 can then learn optimal or preferred operating parameters for the various types of modular devices 9050, generate adjustments to the control programs of the modular devices 9050 in the field, and then transmit (or “push”) updates to the modular devices' 9050 control programs.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, adaptive control of surgical network control and interaction as taught by Shelton, an surgical and interventional planning as taught by Nawana, and incorporate adaptive control program updates for surgical devices as taught by Harris, with the motivation of helping interconnect medical systems and facilities better to ensure patient safety (Harris Para. 0003.)
As per Claim 9, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the method of claim 8, Dugan further teaches wherein the values of the patient biomarker being over or under the post-surgery threshold values are biomarker levels outside of a normal operating range ([Para. 0073] the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter. The feedback system where the feedback system informs the user when a physiological parameter is inside the minimum and maximum threshold values. The feedback system where the feedback system informs the user when the time average of a physiological parameter is exceeds the threshold values.)
Dugan does not explicitly disclose, however Vaccaro discloses
when the patient is performing the post-surgery activity. ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters. [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data (i.e. post-surgery activity), and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters , users receive feedback on post-procedural progress. [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 10, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the method of claim 8, Dugan further teaches wherein the condition is met if the values of the patient biomarker are determined to be over or under the post-surgery threshold values for a predetermined period of time ([Para. 0073] The processing system where the processing system identifies risk values associated with one or more physiological parameters. The processing system where the physiological parameters are selected from the group including: abdominal/body orientation, snoring, blood oxygen, blood pressure, location of center of gravity, physical activity, body heat, altitude tracking, pressure, temperature, respiration, respiration during sleep, tension, and hemodynamic flow. The processing system where the processing system determines risk values by creating a moving average of the physiological parameter data and comparing it to a threshold. The processing system where the moving average calculated over any of a variety of time spans. The processing system where there is a minimum and maximum threshold limitation. The processing system where the processor is coupled with manual inputs. The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter. Examiner interprets the function of when the feedback system informs the user to be indicative of the condition being met.)
Dugan does not explicitly disclose, however Vaccaro discloses
during the duration of the patient's recovery. ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters. [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data (i.e. post-surgery activity), and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters, users receive feedback on post-procedural progress. [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 11, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the method of claim 8, Dugan teaches further comprising: sending the notification alert to a healthcare facility, and wherein the notification alert is accessed by multiple different caregivers to synchronize their handling of the patient within the healthcare facility. ([Para. 0087] an alert from the wearable device to one or more caregivers of the individual upon determining that the physical orientation has not changed by the prescribed amount within a second time interval following the first- time interval. [Para. 0088] the method of Example 7, wherein issuing the alert to the one or more caregivers comprises issuing an alert to a caregiver monitoring station. [Para. 0529] monitoring the body position within the healthcare facility 820 and issuing a first alert 830 from the wearable device 10 through a first wireless communication link of the healthcare facility. For example, the first alert 830 may be a wireless transmission sent from the device to a monitoring station 840 over the facility's wide area network, a personal area network, a Bluetooth communication and the like.)
As per Claim 15, Dugan teaches a computer system for outcome tracking of a patient, comprising:
a processor; ([Para. 0025] a processor.)
and a memory coupled to the processor, the memory storing instructions, that when executed by the processor, cause the computer system to: ([Para. 0072] a memory unit.)
generate an event trigger for the patient, the event trigger corresponds to a condition being met; ([Para. 0029] recorded time series of orientation risk values with the recorded time series of activity risk values to generate a continuous time series of risk values. A cumulative risk may be calculated on a subset of the continuous time series of risk values by calculating a moving average for a subset of the continuous time series of risk values. Thereafter, the processor may be configured to compare the cumulative risk to a cumulative risk threshold value and output a warning when the cumulative risk crosses the cumulative risk threshold value. [Para. 0022] the system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters (biomarker data from sensor(s)). [Para. 0073] informs the user when a risk value exceeds the threshold value for a physiological parameter. [Para. 0162] analyzes a predetermined number of the most recently recorded physiological parameters to determine if one or more of the detected parameters is abnormal as determined over a set period of time. When at least one of the physiological parameters is determined to be abnormal, an alert is generated.)
and based on the values of the patient biomarker being within the post-surgery recovery threshold values when the patient is performing the post-surgery activity, determine whether the condition is met; ([Para. 0022] the physiological parameters recorded by the sensors can include abdominal/body orientation, snoring, blood oxygen, blood pressure, location of center of gravity, activities like running, walking, driving, sleeping, body heat, altitude tracking, pressure readings, temperature readings, and/or user pedometer readings, breathing during sleep, respiration characteristics, tension, temperature (measured at any variety of locations on or in the body), and/or hemodynamic flow restriction. The system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters. [Para. 0025] compare the first cumulative risk value to a first threshold and output a warning when the first cumulative risk value crosses the first threshold. [Para. 0073]The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter.)
based on the condition being met, trigger the event trigger; ([Para. 0073]The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter.)
generate a notification alert corresponding to the event trigger recovery threshold; ([Para. 0025] teaches compare the first cumulative risk value to a first threshold and output a warning when the first cumulative risk value crosses the first threshold.)
Dugan does not explicitly disclose, however Vaccaro discloses
wherein during a duration of a recovery of the patient from a surgical procedure , ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
when the patient is performing a post-surgery activity related to the recovery of the patient; ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data, and a mobile device (e.g., smartphone) including an application configured to receive data from the device.[Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters , users receive feedback on post-procedural progress.)
determine post-surgery complications associated with the recovery of the patient from the surgical procedure; ([Col. 15, Lined 10-17] The collection of the data and storage in the patient's EMR further permits the physician or medical professional to provide a remote watch-dog function, detect complications, detect noncompliance with prescribed therapies, detect other pathologies and otherwise maintain access to patient progress or regression without requiring the physical presence of the patient with the physician or physical therapist.)
receive an indication from the patient sensor system if measured values of the patient biomarker are within the post-surgery recovery threshold values associated with the patient biomarker when the patient is performing the post-surgery activity; ([Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data, and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 32-44] 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in (i.e. threshold) . However, pain reported by the patient remains high, and is, in fact, in the top 15% (i.e. over the threshold values). This condition results in sending prompts (i.e. indication) to both the patient and the physician. The patient is prompted via SMS or a mobile app (i.e. patient sensor system) to reach out to their medical provider. The medical provider is prompted via SMS or a physician user interface to review the patient's chart, and, if necessary, have a member of the staff contact the patient.)
display the real time data analytics, wherein the real time data analytics are displayed via a graph showing patient recovery data during the recovery threshold window; ([Col. 1, Lines 25-31] the comparator 116 of the processor 114 temporally compares the patient's actual post-procedural state to the predictive model of the patient's post-procedural state and outputs the results of the comparison. In one preferred embodiment, the comparison is shown as another line on the temporal trendline graphs of FIGS. 4A and 4B. See, the dot-dash lines in FIGS. 5A and 5B. [Col. 6, Lines 32-37] In the example of FIGS. 5A and 5B, 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in. However, pain reported by the patient remains high, and is, in fact, in the top 15%.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
Dugan/ Vaccaro do not explicitly disclose, however Sampath discloses
send the post-surgery recovery threshold values associated with values of a the patient biomarker to a patient sensor system; ([Para. 0200] A clinician may also use an input device to alter patient monitoring settings such as, for example, options for calculating physiological parameter values from raw data, alarm types, physiological parameter alarm limits (e.g. post-surgery thresholds), etc. Examiner interprets altering the physiological parameter alarm limits to be indicative of sending threshold values.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and incorporate determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, with the motivation of acquiring physiological information from patients, analyzing the physiological information, and communicating the physiological information to clinicians and other systems or devices (Sampath Para. 0002).
Dugan/ Vaccaro/ Sampath do not explicitly teach, however Stoppelkamp teaches
determine post-surgery threshold values associated with a patient biomarker based on the determined post-surgery complications, wherein the post-surgery threshold values are outside of a normal threshold value range;([Pg. 2 Introduction] patients undergoing cardiovascular surgery often are elderly and represent with comorbidities and a weakened general condition. Those patients are therefore especially at risk of complications such as systemic inflammatory response syndrome (SIRS). This generic term encompasses sterile inflammation as well as sepsis (that is SIRS with confirmed bacteremia) and is defined by meeting two or more of the following criteria: 1) a temperature of above 38°C or below 36°C, 2) a heart rate over 90 beats/min, 3) a respiratory rate above 20 breaths/min or decreased paCO2 below 32 mmHg, 4) white blood cell count of over 12000 cells/mm3 or under 4000 cells/mm3 or more than 10% immature neutrophils)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, and incorporate identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, with the motivation of predicting the development of Systemic inflammatory response syndrome (SIRS) available for clinical decision in the early post-operative period or at early hours in the ICU in order to timely counteract the dysregulation of the immune system (Stoppelkamp Pg. 3 Introduction).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp do not explicitly teach, however Shelton teaches
control, via a plurality of first control signals, a plurality of surgical devices; ([Para. 0313] the computer-implemented interactive surgical system is configured to monitor and analyze data related to the operation of various surgical systems that include surgical hubs, surgical instruments (i.e. surgical devices), robotic devices and operating theaters or healthcare facilities. Surgical hubs 7006 that are coupled to the cloud 7004 can be considered the client side of the cloud computing system (i.e., cloud-based analytics system). Surgical instruments 7012 are paired with the surgical hubs 7006 for control and implementation of various surgical procedures or operations.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, and incorporate methods for adaptive control of surgical network control and interaction as taught by Shelton, with the motivation of helping interconnect medical systems and facilities to better improve patient practices (Shelton Para. 0013).
Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton do not explicitly teach, however Nawana teaches
generate, via the patient sensor system, biomarker data and physical state data of the patient; ([Para. 0031] Receiving the information regarding the at least one of the plurality of patient-specific factors can include receiving data from a plurality of sensors. [Para. 0032] The diagnosis and treatment module receiving the information regarding the plurality of symptoms (i.e. physical state) can include receiving data from a plurality of sensors. [Para. 0033] The monitoring can include at least one of vital signs (i.e. biomarker) of the patient.)
generate, via an environmental sensing system, environmental data associated with the surgical procedure; ([Para. 0034] The operation module can provide the electronic feedback on a display, and the operation module can provide additional electronic information regarding the actual performance of the selected invasive treatment on the display including any one or more of a fluoroscopic image of the patient, vital signs of the patient, neural monitoring outputs, surgical techniques videos, camera feeds from outside a room where the selected invasive treatment is being performed, power usage of instruments, and controls for any one or more devices that gather the additional electronic information and provide the additional electronic information to the operation module.)
infer, via a situational awareness system, surgical procedural outcome data based on the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0120] The system 10 can allow paths of an individual's medical treatment through all or part of the continuum 22 to be compared and consolidated then applied to patients with similar symptoms to diagnose and choose the treatment that previously produced a best outcome for similarly situated patients. The outcome can include technical, anatomic, functional, and patient reported parameters.)
output, to a facility analytics system within a recovery threshold window, the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0296] The surgery feedback module 238 can be configured to generate one or more post-op reports summarizing the surgery performed. A post-op report generated for a medical practitioner such as the performing surgeon or the patient's PCP can include medically precise information regarding the surgery and/or the patient, such as the type of surgery performed (i.e. environmental data), the medical devices implanted in the patient, date of the surgery, the medications administered to the patient, projected success rate of the surgery based on historic success rates of the surgery and the patient's particular surgery (i.e. physical state), etc. [Para. 0321] The patient monitoring module 244 can be configured to provide a user with information regarding a patient's post-op treatment plan, such as by displaying post-op treatment plan information on a device in communication with the system 10. Non-limiting examples of post-op treatment plan information that can be displayed on the device include reminders for upcoming post-op appointments (e.g., physical therapy appointments), reminders of days/times to take medication, percentage of overall compliance with the post-op treatment plan, reminders to upload data (e.g., video of exercise, blood pressure and/or other vital sign reading (i.e. biomarker), etc.), current list of symptoms and/or pain levels, etc.)
receive, from the facility analytics system, real time data analytics associated with the biomarker data and the physical state data of the patient, the biomarker data and the environmental data associated with the surgical procedure; ([Para. 0034] The operation module can provide the electronic feedback on a display, and the operation module can provide additional electronic information regarding the actual performance of the selected invasive treatment on the display including any one or more of a fluoroscopic image of the patient, vital signs of the patient, neural monitoring outputs, surgical techniques videos, camera feeds from outside a room where the selected invasive treatment is being performed, power usage of instruments, and controls for any one or more devices that gather the additional electronic information and provide the additional electronic information to the operation module.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, adaptive control of surgical network control and interaction as taught by Shelton, and incorporate an operating room analysis module as taught by Nawana, with the motivation of providing improved systems and methods for surgical and interventional planning, support, post-operative follow-up, and functional recovery tracking (Nawana Para. 0019).
receive an updated control program from the facility analytics system based on the real time data analytics; ([Para. 0298] The surgical hub 9000 can sense or receive perioperative data from the modular devices 9050 and then associate the received perioperative data with surgical procedural outcome data. The perioperative data indicates how the modular devices 9050 were controlled during the course of a surgical procedure. The procedural outcome data includes data associated with a result from the surgical procedure (or a step thereof), which can include whether the surgical procedure (or a step thereof) had a positive or negative outcome. [Para. 0299] The surgical hub 9000 can transmit the associated modular device 9050 data and outcome data to the analytics system 9100 for processing thereon. By transmitting both the perioperative data indicating how the modular devices 9050 are controlled and the procedural outcome data, the analytics system 9100 can correlate the different manners of controlling the modular devices 9050 with surgical outcomes for the particular procedure type. )
and update the control of the plurality of surgical devices, via a plurality of second control signals, based on the updated control program and the inferred surgical procedural outcome data. ([Para. 0299] Based on this paired data, the analytics system 9100 can then learn optimal or preferred operating parameters for the various types of modular devices 9050, generate adjustments to the control programs of the modular devices 9050 in the field, and then transmit (or “push”) updates to the modular devices' 9050 control programs.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan, an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, identification of predictive early biomarkers for complications after cardiovascular surgery as taught by Stoppelkamp, adaptive control of surgical network control and interaction as taught by Shelton, an surgical and interventional planning as taught by Nawana, and incorporate adaptive control program updates for surgical devices as taught by Harris, with the motivation of helping interconnect medical systems and facilities better to ensure patient safety (Harris Para. 0003.)
As per Claim 16, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 15, Dugan further teaches wherein the post-surgery recovery threshold values correspond with an expected operating range ([Para. 0073] the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter. The feedback system where the feedback system informs the user when a physiological parameter is inside the minimum and maximum threshold values. The feedback system where the feedback system informs the user when the time average of a physiological parameter is exceeds the threshold values.)
Dugan does not explicitly disclose, however Vaccaro discloses
when the patient is performing the post-surgery activity. ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters. [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data (i.e. post-surgery activity), and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters , users receive feedback on post-procedural progress. [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 17, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 15, Dugan further teaches wherein the condition is met if the values of the patient biomarker are determined to be within the post-surgery recovery threshold values for a predetermined period of time ([Para. 0073] The processing system where the processing system identifies risk values associated with one or more physiological parameters. The processing system where the physiological parameters are selected from the group including: abdominal/body orientation, snoring, blood oxygen, blood pressure, location of center of gravity, physical activity, body heat, altitude tracking, pressure, temperature, respiration, respiration during sleep, tension, and hemodynamic flow. The processing system where the processing system determines risk values by creating a moving average of the physiological parameter data and comparing it to a threshold. The processing system where the moving average calculated over any of a variety of time spans. The processing system where there is a minimum and maximum threshold limitation. The processing system where the processor is coupled with manual inputs. The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter. Examiner interprets the function of when the feedback system informs the user to be indicative of the condition being met.)
Dugan does not explicitly disclose, however Vaccaro discloses
during the duration of the patient's recovery. ([Col. 2, Lines 55-59] FIG. 1 is a schematic diagram of an apparatus (system 100) for tracking patient recovery following an orthopedic (orthopedic) procedure. The system 100 includes a physical sensor 102 configured to collect pre-procedural and post-procedural walking parameters. [Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data (i.e. post-surgery activity), and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 20-23] The feedback that users receive after the procedure is also an example of gamification. In return for engaging with the user interface and for reporting walking parameters , users receive feedback on post-procedural progress. [Col. 9, Lines 23-32] Data relating to a patient's activity is a good indication of the patient's physical condition, abilities at a certain time and recovery when considered over time during a patient's recovery, particularly for recovery from orthopedic procedures, such as total hip and knee replacements or other extremity procedure. Tracking the patient's movement can be invaluable in the diagnosis and treatment of such recovery and in the general monitoring and maintenance of the patient's health and well-being.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 18, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 15, Dugan further teaches wherein the processor is further configured to send the notification alert to a healthcare facility, and wherein the notification alert is accessed by multiple different caregivers to synchronize their handling of the patient within the healthcare facility. ([Para. 0087] an alert from the wearable device to one or more caregivers of the individual upon determining that the physical orientation has not changed by the prescribed amount within a second time interval following the first- time interval. [Para. 0088] the method of Example 7, wherein issuing the alert to the one or more caregivers comprises issuing an alert to a caregiver monitoring station. [Para. 0529] monitoring the body position within the healthcare facility 820 and issuing a first alert 830 from the wearable device 10 through a first wireless communication link of the healthcare facility. For example, the first alert 830 may be a wireless transmission sent from the device to a monitoring station 840 over the facility's wide area network, a personal area network, a Bluetooth communication and the like.)
As per Claim 23, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Vaccaro further teaches wherein the graph is a line graph, and wherein the line graph shows the values of the patient biomarker changing over time during the recovery threshold window. ([Col. 1, Lines 25-31] the comparator 116 of the processor 114 temporally compares the patient's actual post-procedural state to the predictive model of the patient's post-procedural state and outputs the results of the comparison. In one preferred embodiment, the comparison is shown as another line on the temporal trendline graphs of FIGS. 4A and 4B. See, the dot-dash lines in FIGS. 5A and 5B. [Col. 6, Lines 32-37] In the example of FIGS. 5A and 5B, 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in. However, pain reported by the patient remains high, and is, in fact, in the top 15%. )
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
As per Claim 24, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Vaccaro further teaches wherein:
the post-surgery complications are soft tissue repair associated with the recovery of the patient from the surgical procedure, ([Col. 12, Lines 23-27] Data collection tools 50 connected to an implant may also be utilized to measure mechanical strain and loading forces to detect particular conditions, such as intra-articular conditions conducive to joint wear in vivo. [Col. 15, Lined 10-17] The collection of the data and storage in the patient's EMR further permits the physician or medical professional to provide a remote watch-dog function, detect complications, detect noncompliance with prescribed therapies, detect other pathologies and otherwise maintain access to patient progress or regression without requiring the physical presence of the patient with the physician or physical therapist.))
the post-surgery threshold values are post-surgery loading threshold values at a soft tissue repair location, wherein the post-surgery loading threshold values at the soft tissue repair location are lower than a normal loading value range, ([Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data, and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 32-44] 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in (i.e. threshold) . However, pain reported by the patient remains high, and is, in fact, in the top 15% (i.e. over the threshold values). This condition results in sending prompts (i.e. indication) to both the patient and the physician. The patient is prompted via SMS or a mobile app (i.e. patient sensor system) to reach out to their medical provider. The medical provider is prompted via SMS or a physician user interface to review the patient's chart, and, if necessary, have a member of the staff contact the patient.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
Vaccaro does not explicitly teach, however Sampath teaches
and the post-surgery loading threshold values associated with the patient biomarker are sent to the patient sensor system. ([Para. 0200] A clinician may also use an input device to alter patient monitoring settings such as, for example, options for calculating physiological parameter values from raw data, alarm types, physiological parameter alarm limits (e.g. post-surgery thresholds), etc. Examiner interprets altering the physiological parameter alarm limits to be indicative of sending threshold values.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and incorporate determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, with the motivation of acquiring physiological information from patients, analyzing the physiological information, and communicating the physiological information to clinicians and other systems or devices (Sampath Para. 0002).
As per Claim 25, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Vaccaro further teaches wherein:
the post-surgery complications are moisture exposure against infection or premature suture failure associated with the recovery of the patient from the surgical procedure,([Col. 12, Lines 18-21] . Data collection tools 50 that are attached to implants could be configured such that the monitoring chip 30 detects the presence of infection. [Col. 15, Lined 10-17] The collection of the data and storage in the patient's EMR further permits the physician or medical professional to provide a remote watch-dog function, detect complications, detect noncompliance with prescribed therapies, detect other pathologies and otherwise maintain access to patient progress or regression without requiring the physical presence of the patient with the physician or physical therapist.)
the post-surgery threshold values are post-surgery moisture exposure threshold values, wherein the post-surgery moisture exposure threshold values are lower than a normal moisture exposure range, ([Col. 3, Lines 58-62] the physical sensor 102 includes a device worn by the patient and configured to collect movement/motion data, and a mobile device (e.g., smartphone) including an application configured to receive data from the device. [Col. 6, Lines 32-44] 6 months after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value and within the bounds that 50% of patients will be in (i.e. threshold) . However, pain reported by the patient remains high, and is, in fact, in the top 15% (i.e. over the threshold values). This condition results in sending prompts (i.e. indication) to both the patient and the physician. The patient is prompted via SMS or a mobile app (i.e. patient sensor system) to reach out to their medical provider. The medical provider is prompted via SMS or a physician user interface to review the patient's chart, and, if necessary, have a member of the staff contact the patient.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
Vaccaro does not explicitly teach, however Sampath teaches
and the post-surgery moisture exposure threshold values associated with the patient biomarker are sent to the patient sensor system. ([Para. 0200] A clinician may also use an input device to alter patient monitoring settings such as, for example, options for calculating physiological parameter values from raw data, alarm types, physiological parameter alarm limits (e.g. post-surgery thresholds), etc. Examiner interprets altering the physiological parameter alarm limits to be indicative of sending threshold values.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, and incorporate determining an alarm threshold adapted to monitor for the physiological parameters of patients as taught by Sampath, with the motivation of acquiring physiological information from patients, analyzing the physiological information, and communicating the physiological information to clinicians and other systems or devices (Sampath Para. 0002).
Claim(s) 5 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dugan (US 20230113555 A1) in view of Vaccaro (US 11328806 B2) in view of Sampath (US 20180174680 A1) in view of Stoppelkamp (Identification of Predictive Early Biomarkers for Sterile-SIRS after Cardiovascular Surgery (2015)) in view of Shelton (US 20190206563 A1) in view of Nawana (US 20190216452 A1) in view of Harris (US 20190206003 A1) in view of Mazar (US 20150302538 A1).
As per Claim 5, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris the computer system of claim 1, Dugan further teaches wherein the event trigger is an emergency event trigger, and the condition associated with the emergency event trigger is met if the values of the patient biomarker are determined to be a predetermined amount over or under the post-surgery threshold values, ([Para. 0029] recorded time series of orientation risk values with the recorded time series of activity risk values to generate a continuous time series of risk values. A cumulative risk may be calculated on a subset of the continuous time series of risk values by calculating a moving average for a subset of the continuous time series of risk values. Thereafter, the processor may be configured to compare the cumulative risk to a cumulative risk threshold value and output a warning when the cumulative risk crosses the cumulative risk threshold value. [Para. 0022] the system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters (biomarker data from sensor(s)). [Para. 0073] The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter [Para. 0162] a predetermined number of the most recently recorded physiological parameters to determine if one or more of the detected parameters is abnormal as determined over a set period of time. When at least one of the physiological parameters is determined to be abnormal, an alert is generated.)
Dugan does not explicitly disclose, however Mazar
and wherein the notification alert corresponding to the emergency event trigger indicates an emergency and that immediate action be taken. ([Para. 0012] If the readings are outside of an acceptable range for the patient, the monitor can send an alert to one or more caregivers to inform the caregivers that an emergency situation associated with the patient (such as, for example, cardiac arrest) is occurring.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate streamlining and integrating patient care and health information management systems as taught by Mazar, with the motivation of monitoring patient stability and status, as well as allowing for coordination of care in a patient-centric matter (Mazar Para. 0004 and Para. 0007).
As per Claim 12, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/
Harris the method of claim 8, Dugan further teaches wherein the event trigger is an emergency event trigger, and the condition associated with the emergency event trigger is met if the values of the patient biomarker are determined to be a predetermined amount over or under the post- surgery threshold values, ([Para. 0029] recorded time series of orientation risk values with the recorded time series of activity risk values to generate a continuous time series of risk values. A cumulative risk may be calculated on a subset of the continuous time series of risk values by calculating a moving average for a subset of the continuous time series of risk values. Thereafter, the processor may be configured to compare the cumulative risk to a cumulative risk threshold value and output a warning when the cumulative risk crosses the cumulative risk threshold value. [Para. 0022] the system is configured to establish various risk thresholds, which can be based on one or more of these physiological parameters (biomarker data from sensor(s)). [Para. 0073] The feedback system where the feedback system informs the user when a risk value exceeds the threshold value for a physiological parameter [Para. 0162] a predetermined number of the most recently recorded physiological parameters to determine if one or more of the detected parameters is abnormal as determined over a set period of time. When at least one of the physiological parameters is determined to be abnormal, an alert is generated.)
Dugan does not explicitly disclose, however Mazar
and wherein the notification alert corresponding to the emergency event trigger indicates an emergency and that immediate action be taken. ([Para. 0012] If the readings are outside of an acceptable range for the patient, the monitor can send an alert to one or more caregivers to inform the caregivers that an emergency situation associated with the patient (such as, for example, cardiac arrest) is occurring.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate streamlining and integrating patient care and health information management systems as taught by Mazar, with the motivation of monitoring patient stability and status, as well as allowing for coordination of care in a patient-centric matter (Mazar Para. 0004 and Para. 0007).
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dugan (US 20230113555 A1) in view of Vaccaro (US 11328806 B2) in view of Sampath (US 20180174680 A1) in view of Stoppelkamp (Identification of Predictive Early Biomarkers for Sterile-SIRS after Cardiovascular Surgery (2015)) in view of Shelton (US 20190206563 A1) in view of Nawana (US 20190216452 A1) in view of Harris (US 20190206003 A1) in view of Ziegler (US 20110319723 A1).
As per Claim 21, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Vaccaro further teaches dates when the values of the patient biomarker are over or under the post-surgery threshold values during the recovery threshold window. ([Col. 6, Lines 29-37] the comparison is shown as another line on the temporal trendline graphs of FIGS. 4A and 4B. See, the dot-dash lines in FIGS. 5A and 5B. In the example of FIGS. 5A and 5B, 6 months (i.e. recovery threshold window) after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value (i.e. within the threshold values) and within the bounds that 50% of patients will be in (i.e. threshold). However, pain reported by the patient remains high, and is, in fact, in the top 15% (i.e. over the threshold values). [Col. 13, Lines 40-44] data collection tools 50 are able to acquire consistent walking and movement information from the patient, particularly post-operative walking or movement activity. FIGS. 9A-9D, taken together, provide examples of graphic displays of information the data collection tools 50 may acquire. Figures 9A and 9B also contain specific dates of walking and movement data. Examiner interprets the period of 6 months to be indicative of dates.)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
Vaccaro does not explicitly disclose, however Ziegler discloses
wherein the graph is a bar graph, and wherein the bar graph shows ([Para. 0020] FIGS. 2A and 2B show bar graphs of total atrial arrhythmia burden (that is, how much time out of a day is spent in a state of atrial tachycardia or atrial fibrillation) obtained from PCDs implanted in patients A and B, respectively. The atrial arrhythmia burden in each patient was measured over an extended period of time (approximately one year).)
Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time of the invention was made to combine the bar graph of Ziegler with the teaching of Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton since the combination of the references is merely simple substitution of one known element for another producing a predictable result (KSR rationale B). Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is, in the substitution of the bar graph of Ziegler for the line graph of Vaccaro. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dugan (US 20230113555 A1) in view of Vaccaro (US 11328806 B2) in view of Sampath (US 20180174680 A1) in view of Stoppelkamp (Identification of Predictive Early Biomarkers for Sterile-SIRS after Cardiovascular Surgery (2015)) in view of Shelton (US 20190206563 A1) in view of Nawana (US 20190216452 A1) in view of Harris (US 20190206003 A1) in view of Olsen (US 9750442 B2).
As per Claim 22, Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton/ Nawana/ Harris teach the computer system of claim 1, Vaccaro further teaches corresponding to when the values of the patient biomarker are within the post-surgery threshold values during the recovery threshold window and when the values of the patient biomarker are over or under the post-surgery threshold values during the recovery threshold window. ([Col. 6, Lines 29-37] the comparison is shown as another line on the temporal trendline graphs of FIGS. 4A and 4B. See, the dot-dash lines in FIGS. 5A and 5B. In the example of FIGS. 5A and 5B, 6 months (i.e. recovery threshold window) after 2-level Anterior Cervical Discectomy and Fusion (ACDF) procedure to treat cervical myelopathy, the patient's daily step count is near the predicted value (i.e. within the threshold values) and within the bounds that 50% of patients will be in (i.e. threshold). However, pain reported by the patient remains high, and is, in fact, in the top 15% (i.e. over the threshold values).)
Therefore, it would be prima facie obvious to one of ordinary skill in the art, at the time of filing, to modify the method of monitoring the physical orientation of an individual as taught by Dugan and incorporate an apparatus that tracks patient recovery following an orthopedic procedure as taught by Vaccaro, with the motivation of accurately predicting a patient's recovery process (Vaccaro Col. 1, Lines 43-44).
Vaccaro does not explicitly disclose, however Olsen discloses
wherein the graph is a pie graph, and wherein the pie graph shows percentages of time ([Col. 2, Lines 63-64] The physiological parameter is oxygen saturation. [Col. 3, Lines 35-39] FIG. 7 is an illustration of a single-patient, single-parameter physiological status monitor displaying a pie-chart having a height that represents the total monitored time interval and pie slices that each represent the percentage of time a parameter is within the specified value range. [Col. 4, Lines 41-43] The range categories 138 have predetermined value ranges and corresponding percentages of time that the selected parameter 132 spent in each range.)
Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time of the invention was made to combine the pie chart of Olsen with the teaching of Dugan/ Vaccaro/ Sampath/ Stoppelkamp/ Shelton since the combination of the references is merely simple substitution of one known element for another producing a predictable result (KSR rationale B). Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is, in the substitution of the pie chart of Olsen for the line graph of Vaccaro. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Response to Arguments
Applicant's arguments, see pgs. 11-12 “Rejections under 35 U.S.C. 103” filed 09/11/2025 have been fully considered have been have been fully considered and are persuasive regarding the newly added limitations. Therefore, the rejection has been withdrawn. However, upon further consideration, a new grounds of rejection is made in view of newly added references Nawana and Harris, as per the rejection above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/P.K.E./Examiner, Art Unit 3682
/PETER H CHOI/Supervisory Patent Examiner, Art Unit 3681