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 .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-24 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mallon et al (US PUB. 20120259648, herein Mallon).
Regarding claim 1, Mallon teaches A computer-implemented method comprising, using one or more processing devices:
receiving a plurality of sets of data corresponding to respective users of a plurality of users undergoing rehabilitation treatment, wherein the treatment uses the respective treatment devices, and wherein each of the sets of data includes sensor data obtained while the respective users perform respective treatment plans and the plurality of sets of data is received in real-time or near real-time as the respective users perform the respective treatment plans (0031 “motion sensors, physiologic sensors, or both are methodically tested and correlated with specific activities, exercises, movements, intended outcomes, etc., in order to determine optimized sensor combinations for each activity, exercise and/or movement, and in certain embodiments, for each individual or certain groups of individuals. The sensors are configured to wirelessly communicate with a gateway, which in turn communicates directly or via a smartphone with a remote server. The gateway can be a dedicated device, a multipurpose device such as a smartphone, or it can be a dedicated device configured to be attached to the smartphone. For example, in the physical therapy arena, the sensors can detect when a patient has properly setup and completed an exercise and can transmit such data to the remote server via the gateway”);
storing, as objective information, the plurality of sets of data in a queryable data format (0016 “a database configured to store prescription and treatment information, sensor data, subject information, reporting, and billing information for a plurality of subjects; a server coupled with the database and the communication interface, the server configured to: receive subject data via the communication interface, the subject data comprising a subject identifier identifying a particular subject and diagnosis information, create a record in the database for the subject using the subject identifier and the diagnosis information, receive sensor data via the communication interface, the sensor data including data related to certain activities, exercises or movements performed by the subject, analyze the sensor data to establish a baseline assessment, and develop at least partially a treatment plan based on the sensor data and the baseline assessment and subject data”);
receiving first sensor data associated with the performance, by a first user using a first treatment device, of a first treatment plan, wherein the first treatment plan corresponds to a standardized treatment plan assigned to the user based on a classification of the user, and wherein the first sensor data correlates with the objective information stored in the queryable data format (0047 “a patient or individual can be outfitted with one or more sensors designed to monitor the activities, exercises and movements they perform. The sensors can then communicate data related to the activities, exercises and movements, as well as other types of data, to server 102 where it can be stored and analyzed and where reports and messages can be generated, treatment plans assessed and modified, and billing performed as needed”);
providing the objective information and the first sensor data to a machine learning model trained to predict, based on the objective information and the first sensor data, a likelihood of the first user achieving a rehabilitation goal associated with the rehabilitation treatment (0124 “algorithms 116, which can increase the predictive ability of algorithms 116. Thus, algorithms 116 can be configured to mine data for a plurality of individuals and to assess patterns, trends, correlations, etc., and to apply them to the data being received from sensors 202 for a given patient or individual. Algorithms 116 can then use this analysis to predict or forecast results for the patient or individual, to predict or forecast required changes, modifications, etc., to the treatment plan; to determine progress; to determine whether the patient or individual is ready to advance to another level; etc.”);
generating, based on the objective information, the first sensor data, and the likelihood of the first user achieving the rehabilitation goal, a second treatment plan (0124 “algorithms 116, which can increase the predictive ability of algorithms 116. Thus, algorithms 116 can be configured to mine data for a plurality of individuals and to assess patterns, trends, correlations, etc., and to apply them to the data being received from sensors 202 for a given patient or individual. Algorithms 116 can then use this analysis to predict or forecast results for the patient or individual, to predict or forecast required changes, modifications, etc., to the treatment plan; to determine progress; to determine whether the patient or individual is ready to advance to another level; etc.”);
and controlling, based on the second treatment plan, the first treatment device (0129 “a patient or individual at remote location 106 performing various activities, exercises or movements in accordance with his or her treatment plan can receive a feedback message in auditory, textual or image form on or through, e.g., gateway 207 that the patient or individual is not performing the exercises correctly. This feedback message can be provided directly from server 102 by comparing the patient's or individual's incoming data from sensors 202 against his or her currently prescribed treatment plan or historic or population data stored in storage system 110. In some embodiments, the sensors 202 themselves can be configured to provide an indication to the server 102 that the patient or individual is performing the exercises incorrectly--such as if the sensors 202 send satisfactory signals 204 intermingled with a certain threshold of unsatisfactory signals”, 0126 “a diagram illustrating an example process for analyzing the sensor data in accordance with one embodiment. First, in step 902 sensor data is received from sensors 202, e.g., via gateway 207. In step 904, the data can be analyzed to determine compliance with the associated treatment plan. In addition, a determination can be made as to whether the patient or individual is progressing, or regressing (step 910); whether the patient or individual is ready to advance to a next level within the treatment plan (step 912); whether the treatment plan needs to change (step 914); etc. As explained, this can be done by simply analyzing the data in step 906 or, as illustrated in step 908, by comparing the data to past data for the patient or individual, or a combination of steps 906 and 908.”).
Regarding claim 2, the cited prior art teach The computer-implemented method of claim 1.
Mallon teaches wherein the objective information is stored based on diagnostic requirements associated with the rehabilitation treatment (0016 0017).
Regarding claim 3, the cited prior art teach The computer-implemented method of claim 1.
Mallon teaches wherein the objective information is stored in a standardized or canonical format (0090).
Regarding claim 4, the cited prior art teach The computer-implemented method of claim 1.
Mallon teaches further comprising: generating a prompt in response to a determination that a component of the sensor data exceeds a threshold; determining, based on the objective information and the sensor data, a cause of the component exceeding the threshold; and based on the determined cause, at least one of (i) controlling the first treatment device to mitigate the cause and (ii) providing an instruction to the first user (0129 “in some embodiments, system 100 includes the ability to provide feedback and or messaging to and/or between interested parties 104, 106, 112, 120, etc. For example, a patient or individual at remote location 106 performing various activities, exercises or movements in accordance with his or her treatment plan can receive a feedback message in auditory, textual or image form on or through, e.g., gateway 207 that the patient or individual is not performing the exercises correctly. This feedback message can be provided directly from server 102 by comparing the patient's or individual's incoming data from sensors 202 against his or her currently prescribed treatment plan or historic or population data stored in storage system 110. In some embodiments, the sensors 202 themselves can be configured to provide an indication to the server 102 that the patient or individual is performing the exercises incorrectly--such as if the sensors 202 send satisfactory signals 204 intermingled with a certain threshold of unsatisfactory signals”)
Regarding claim 5, the cited prior art teach The computer-implemented method of claim 4.
Mallon teaches further comprising providing the prompt to a user interface associated with a medical professional and receiving, via the user interface, at least one of (i) control parameters for the first treatment device and (ii) the instruction to the first user (0034 “"treatment plan" is intended to refer to any kind of activity, movement or exercise plan provided to an individual by a supervisor such as a physical therapist, occupational therapist, physician, personal trainer, coach, wellness expert, etc. Thus, while the terms "prescribed treatment" and "prescribed treatment plan" can refer to a treatment or plan that is associated with a prescription from a healthcare provider, it can also simply refer to an exercise regimen or routine provided by an, e.g., personal trainer.”, 0059-0060).
Regarding claim 6, the cited prior art teach The computer-implemented method of claim 1.
Mallon teaches further comprising: receiving qualitative information corresponding to the respective users; converting the qualitative information to second objective information; and storing the second objective information in the queryable data format (0098 “database 110 can store algorithms or applications that enable server 102 to generate feedback, instruction, intervention, or compliance messaging as well as targeted advertising that can be sent to the patient or individual, healthcare provider, insurance provider, etc., as well as to manage billing, payments and reimbursement. FIGS. 4-9 and the descriptions that follow describe some of the processes that can be carried out by server 102 using algorithms 116 as well as detailed examples of movement management and monitoring the can be performed within system 100”, 0099 “baseline assessment can involve the creation of an avatar that can then be used later on for visual instruction, feedback and motivation as well as final stage assessment. A patient or individual can be required to visit a supervised location 104 for baseline assessment. For example, in the case of physical therapy, a prescribing healthcare provider, e.g., a physician can provide a "prescription" for physical therapy to the patient in his or her office for a specific, individualized treatment plan for the patient or the patient can take it to another healthcare provider, e.g., a physical therapist, whom then develops a specific, individualized treatment plan for the patient. In other words, the, e.g., physician or physical therapist can evaluate a patient and develop a specific, individualized treatment plan based upon the patient's particular circumstances”).
Regarding claim 7, the cited prior art teach The computer-implemented method of claim 6.
Mallon teaches further comprising determining a correlation between the qualitative information and the second objective information and converting, based on the correlation, the qualitative information to the second objective information (0055 “device 205 can be configured to not only aggregate the data but to also correlate the data, e.g., from different sensors, based on time stamps or other information included in the data. Device 205 can also be configured to filter the data, and to identify critical information, such alarm conditions, most relevant data, etc. It should be noted that device 205 can comprise multiple antenna 220, receiver/transmitters 222, or both in order to aggregate data from multiple motion sensors 202 some of which can be transmitting in one particular frequency band, such as the ISM Band in the 902 to 928 MHz frequency band, while others are transmitting in another frequency band or using a different protocol, such as Bluetooth data, which operates in the 2.4 GHz range. It will also be understood that multiple antennas or receivers can be used to provide diversity to improve reception”, 0124 “algorithms 116 can be configured to mine data for a plurality of individuals and to assess patterns, trends, correlations, etc., and to apply them to the data being received from sensors 202 for a given patient or individual. Algorithms 116 can then use this analysis to predict or forecast results for the patient or individual, to predict or forecast required changes, modifications, etc., to the treatment plan; to determine progress; to determine whether the patient or individual is ready to advance to another level; etc”).
Regarding claim 8, the cited prior art teach The computer-implemented method of claim 7.
Mallon teaches wherein the qualitative information corresponds to pain levels reported by the respective users (0065 “combinations of sensors can be deployed for use in conjunction with the systems and methods described herein. For example, various motion sensors, strength sensors, physiologic sensors such as heart rate sensors, blood pressure sensors, skin conductance or perspiration rate sensors, temperature sensors, pain sensors and oxygen sensors, etc., e.g., for detecting blood oxygen level, cameras, etc., can be worn, held, attached or tethered to the patient or individual, or external to the patient or users”).
Claims 9-24 are rejected using similar reasoning as the rejection of claims 1-8 due to reciting similar limitations but directed towards a system and a computer readable non-transitory media.
Conclusion
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/TAMEEM D SIDDIQUEE/
Primary Examiner
Art Unit 2116
Prosecution Insights