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 .
Claim Objections
Claims 8 and 14 objected to because of the following informalities:
“refiling” should read “refilling”. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
MPEP 2161.01 I. recites in part:
"... original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection IV. .."
The following limitations define the invention in functional language, but the specification lacks the algorithm or steps/procedure for performing the functions or are not explained in sufficient detail:
Regarding claim 1, the limitation “performing a predictive analysis on the physiological and behavioral data through the AI processing module, and identifying activities of daily living (ADLs) of the patient through a gesture-detection module” lacks a proper written description.
Regarding claim 1, the limitation “detecting abnormality actions of the patient based on the physiological and behavioral data and the ADLs through the AI processing module, thereby generating insights and predictive analytic reports for the patient” lacks a proper written description.
Independent claims 13 and 20 feature limitations similar to those of claim 1, and are therefore rejected using the same rationale.
Dependent claims are rejected as well since they inherit the limitations of the independent claims.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the limitation “performing a predictive analysis on the physiological and behavioral data through the AI processing module, and identifying activities of daily living (ADLs) of the patient through a gesture-detection module” is indefinite. The manner in which the claim is written renders the metes and bounds of the claim unclear. It is unclear if the claim consists of two separate functions of performing a predictive analysis, and identifying ADL’s, or if the limitation consists of a single function of identifying ADLs based on predictive analysis. For sake of examination, the Examiner shall assume the latter. Further it is unclear as to how “predictive analysis” (i.e., prediction of an upcoming action) relates to detection of a current action (i.e., ADL currently performed by patient).
Regarding claims 1 and 5, the limitations “analyzing medical data of the patient to identify baseline data of the patient through the AI processing module”, “detecting abnormality actions of the patient based on the physiological and behavioral data and the ADLs through the AI processing module, thereby generating insights and predive analytic reports for the patient”, and “The system of claim 1, wherein the AI processing module is further configured to detect patient’s abnormality actions based on deviation in the physiological and behavioral data of the patient with respect to the baseline data” are indefinite. It is unclear as to how it may be determined that a first particular type of data (i.e., physiological and behavioral data) deviates from a second type of data (i.e., baseline data based on medical data). For sake of examination, the Examiner shall interpret the “medical data” as being “physiological and behavioral data”.
Regarding claim 4, the limitation “The system of claim 1, wherein the gesture-detection module is configured to perform predictive analysis to detect the ADLs…” is indefinite. Claim 1 features the limitation “performing a predictive analysis on the physiological and behavioral data through the AI processing module, and identifying activities of daily living (ADLs) of the patient through a gesture-detection module”. It is unclear if the predictive analysis performed by the gesture-detection module (claim 4) is the same as the predictive analysis performed by the AI processing module (claim 1). Further it is unclear as to how “predictive analysis” (i.e., prediction of an upcoming action) relates to detection of a current action (i.e., ADL currently performed by patient).
The term “intensity” in claims 4 and 18 is a relative term which renders the claim indefinite. The term “intensity” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Regarding claim 10, the limitation “…wherein the patient monitoring device comprises a plurality of holders that are mounted on both sides of the patient monitoring device…” is indefinite. Aside from being described as having a processor and memory, the claims have featured no structural description of the patient monitoring device. Thus is unclear as to what is considered a “side” of the patient monitoring device.
Claim 11 recites the limitation "…the abnormality actions that is associated with medication adherence" There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 12, the phrase "such as" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
Claim 12 recites the limitation "…the potential medication non-adherence" There is insufficient antecedent basis for this limitation in the claim.
The term “potential medication non-adherence” in claim 12 is a relative term which renders the claim indefinite. The term “potential” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Regarding claim 12, the limitation “The system of claim 11, wherein the gesture-detection module is configured to compare the captured video or image data with the schedule data to identify the timing and frequency of medication adherence events to identify the potential medication non-adherence, such as missed doses or potential overdoses, thereby provide the alerts or reminders in a form of at least one of audios, videos, notifications, and calls to the authorized person” is indefinite. The manner in which the claim is written renders the metes and bounds of the claim unclear; particularly in light of the use of relative terminology and issues regarding antecedent basis as indicated above. For sake of examination, the Examiner shall interpret the limitation as “The system of claim 11, wherein the gesture-detection module is configured to compare the captured video or image data with the schedule data to identify the timing and frequency of medication adherence events”.
Independent claims 13 and 20 feature limitations similar to those of claim 1, and are therefore rejected using the same rationale.
Claim 17 features limitations similar to those of claim 5, and is therefore rejected using the same rationale.
Dependent claims are rejected as well since they inherit the limitations of the independent claims.
Claim limitations featuring “modules” (i.e., artificial intelligence processing module, monitoring module, etc.) and “units” (i.e., capturing unit) invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The written description fails to provide any details regarding the structure of any of the claimed “modules” or “units”. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
A system for monitoring patient’s health in real-time, comprising:
receiving physiological and behavioral data of a patient in real-time
analyzing medical data of the patient to identify baseline data of the patient
performing a predictive analysis on the physiological and behavioral data through the AI processing module, and identifying activities of daily living (ADLs) of the patient
detecting abnormality actions of the patient based on the physiological and behavioral data and the ADLs
allowing an authorized person to enter prescription data and schedule data
dispensing one or more medications through an outlet
identifying the one or more medications that are dispensed through the outlet
transmitting one or more alerts to the authorized user
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recites (additional elements crossed out):
The above limitations as drafted, is a process that, under its broadest reasonable interpretation covers managing personal behavior or relationships or interactions between people, and mental processes. That is, other than reciting the steps as being performed by a “a processor and a memory” of a patient monitoring device, and several “modules” nothing in the claim precludes the steps as being described as managing personal behavior or relationships or interactions between people, and mental processes. For example, but for the recited computing language, the limitations describe a system for observing a patient, providing prescribed medications to the patient, and providing alerts regarding abnormal activities by the patients. The limitations describe the management of personal behavior, as well as actions that can be performed mentally or with pen and paper. If a claim limitation, under its broadest reasonable interpretation, describes managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activities” grouping of abstract ideas. Further, if a claim limitation, under its broadest reasonable interpretation, describes steps that may be performed mentally or with pen and paper, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of a “a processor and a memory” of a patient monitoring device, and several “modules” to perform the steps. These additional elements are recited at a high level of generality (see at least Para. [0033]) such that it amounts to no more than mere instructions to apply the exception using generic computing components. The Examiner notes that the specification provides no details regarding the structure of the “modules” at all.
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. More specifically, the additional elements fail to include (1) improvements to the functioning of a computer or to any other technology or technical field (see MPEP 2106.05(a)), (2) applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition (see Vanda memo), (3) applying the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)), (4) effecting a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)), or (5) applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (see MPEP 2106.05(e) and Vanda memo).
Rather, the limitations merely add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) or generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), particularly as it relates to the recited “processor and memory”, and “modules” elements. This is not sufficient to amount to significantly more than the judicial exception. The claims are therefore still directed to an abstract idea.
Claims 13 and 20 feature limitations similar to those of claim 1 and are therefore also found to be directed to an abstract idea without significantly more.
Claims 2-12 are dependent on claim 1 and include all the limitations of claim 1. Therefore, they are also directed to the same abstract idea. Claims 14-19 are dependent on claim 13, and include all the limitations of claim 13. Claim 3 recites “wherein the monitoring module is configured to capture real-time images or videos of the patient, and transmit the captured real-time images to the AI processing module to confirm the identity of the patient”. Claim 6 recites, “wherein the one or more biomedical devices are configured to communicate with the patient monitoring device via the network…”. Claim 9 recites, “an output module that is adapted to transmit the schedule data…”. However, these equate to mere data gathering, and transmission of data, which is insignificant extra-solution activity. Claim 10 recites “wherein the patient monitoring device comprises a plurality of holders that are mounted on both sides of the patient monitoring device, wherein each holder is configured holding at least one medicine, wherein each holder is configured with at least one sensor that is configured for at least one of an inventory control, a dosage verification, and detecting empty or missing the medicine”. However, this is amounts to no more than mere instructions to apply the exception using generic computing components. The remaining dependent claims recite no further additional elements, and the previously identified additional elements do not integrate the abstract idea of the remaining dependent claims into a practical application, and thus they are also directed to an abstract idea. Therefore, the dependent claims are found to be directed to an abstract idea without significantly more.
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) 1-3, 5-15, 17, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Deterding (US 2021/0043321) in view of Gellman (US 11,554,081).
A system for monitoring patient’s health in real-time, comprising:
a patient monitoring device having a processor and a memory for storing one or more instructions executable by the processor, wherein the patient monitoring device is in communication with a server via a network, wherein the processor is configured to perform one or more operations include:
receiving physiological and behavioral data of a patient in real-time through an artificial intelligence (AI) processing module from a monitoring module and one or more biomedical devices;
analyzing medical data of the patient to identify baseline data of the patient through the AI processing module;
performing a predictive analysis on the physiological and behavioral data through the AI processing module, and identifying activities of daily living (ADLs) of the patient through a gesture-detection module;
detecting abnormality actions of the patient based on the physiological and behavioral data and the ADLs through the AI processing module, thereby generating insights and predictive analytic reports for the patient;
transmitting one or more alerts to the authorized user through an alert module upon detection of the abnormality actions of the patients.
(See at least Para. [0038] – “Some embodiments of the present disclosure provide the following advantages: (1) real time or almost real time monitoring of a patient's physiological data separately or in combination with environmental data for an environment in the vicinity of the patient,… (4) application of one or more adaptive learning algorithms from machine learning methodologies to detect patterns in the patient's physiological data separately or in combination with environmental data.”, Para. [0039] – “In some embodiments, the system may first establish a physiological baseline for a patient by measuring the above parameters during a healthy state. Algorithmic calculation of real time data inputs from a wearable device can identify quantifiable deviations from the baseline and allow determination of health status at any given point in time. If health status deviates ( e.g., more than a set percentage or less than a set percentage) from the baseline, an alert will be wirelessly transmitted to portable electronic devices of care givers.”, Para. [0043] – “As described in more detail below, monitoring devices worn by users 140 can monitor a variety of physiological parameters which can be transmitted to monitoring and feedback platform 130 and/or reporting devices ll0A-ll0N for analysis.”, Para. [0048] – “The baseline profiles may be related to ranges of awake movement intensity e.g., resting, walking or running. Movement intensity and states are useful in defining health and wellness.”, Para. [0055] – “Physiological information sensed from a patient is sent to a remote server by either a wearable device or a mobile device worn coupled to a user. In some embodiments, a local hub or a router within wireless range from the user can connect to the remote server and transmit the physiological information. After the physiological information is received by the remote server, this information is stored on the server. In some embodiments, this information is first processed by a pre-processing algorithm to eliminate artifacts in the information. In some embodiments, machine learning algorithms are applied on the pre-processed information. Examples of machine learning algorithms can include, but not limited to, feature extraction, patent recognition, and causality analysis. (See FIG. 13 for an example).”
Deterding does not explicitly disclose:
allowing an authorized person to enter prescription data and schedule data via a user interface of the patient monitoring device for creating a patient profile;
dispensing one or more medications through an outlet of the patient monitoring device based on the prescription data, and the schedule data upon patient authentication by the gesture-detection module;
identifying the one or more medications that are dispensed through the outlet via an identification module, thereby ensuring to dispense prescribed medication for the patient, which results in improving medication adherence; and
(See Gellman, at least Col. 3, Lines 59-67 and Col. 4, Lines 1-4 - “The dispensing display 20 may comprise a touch screen that allows for user/patient interface with the dispensing device 10, along with or alternatively to option buttons/input 18. In addition to or alternatively to the display 20, the user or patient may interface with the dispensing device 10 via an application loaded on an external device and/or cloud-based server (see external device 160 and server 162 in FIG. 9) to provide some or all of the interface functionality of display 20/buttons 18. Such functionality includes, but is not limited to: adding new medications to dispense, setting the schedule at which the medications will be dispensed, entering patient information, confirming the dispensing of said medication, etc.”, and Col. 10, Lines 61-67 and Col. 11, Lines 1-4 - “One or more cameras 206/216 may also be included for verifying that a pill was dispensed and/or taking a picture of the user to verify the patient is the correct person to dispense the pills for. In one configuration, the user merely walks up to the device and using an identification means (e.g. facial recognition (via camera 206), voice recognition (via microphone—not shown), fingerprint recognition (via camera/scanner) or the like), and the dispensing device 200 identifies the user and dispenses the medication for the detected user based on the indicated medication to be dispensed at the time, ensuring chain of custody.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding to utilize the teachings of Gellman since it may assist in tracking adherence to medications (see at least Para. [0040] of Deterding).
Regarding claim 2, Deterding does not explicitly disclose The system of claim 1, wherein the identification module is adapted to receive at least one of video and image data of one or more dispensed medications from at least one capturing unit, thereby accurately identifying the dispensed medicine using the AI processing module. (See Gellman, at least Col. 5, Lines 51-58 – “As the pill falls, it passes a sensor 136 (e.g. optical sensor such as an IR light and photodiode shown in FIG. 3 and FIG. 4) to allow for indication of whether a pill is successfully dispensed, as well as tally the number of pills being dispensed. To ensure that the dispensed pill was ingested, camera 20 may take an image or video, and store image/video data in memory 156 or cloud-based server 162 (see FIG. 9).” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding to utilize the teachings of Gellman since it may assist in tracking adherence to medications (see at least Para. [0040] of Deterding).
Regarding claim 3, Deterding does not explicitly disclose The system of claim 1, wherein the monitoring module is configured to capture real-time images or videos of the patient, and transmit the captured real-time images to the AI processing module to confirm the identity of the patient. (See Gellman, at least Col. 8, Lines 37-47 – “One or more cameras 20 may be employed for verifying that a pill was dispensed and/or taking a picture of the user to verify the patient is the intended/correct patient. In one configuration, the user simply walks up to the dispensing device 10, and using facial recognition provided in application software 154 the dispensing device 10 administers the medication for the detected user. As the pill cup 24 is removed, the camera 20 may record a video of the user ingesting the medication. This may be stored in memory 156 or cloud, and serve as a log that the medication was taken and by the correct person” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding to utilize the teachings of Gellman since it may assist in tracking adherence to medications (see at least Para. [0040] of Deterding).
Regarding claim 5, in light of the 112 rejection, Deterding discloses The system of claim 1, wherein the AI processing module is further configured to detect patient’s abnormality actions based on deviation in the physiological and behavioral data of the patient with respect to the baseline data. (See at least Para. [0039] – “In some embodiments, the system may first establish a physiological baseline for a patient by measuring the above parameters during a healthy state. Algorithmic calculation of real time data inputs from a wearable device can identify quantifiable deviations from the baseline and allow determination of health status at any given point in time.”)
Regarding claim 6, Deterding discloses The system of claim 1, wherein the monitoring module is configured to continuously track the physiological and behavioral data of the patient remotely in real-time, wherein the one or more biomedical devices are configured to communicate with the patient monitoring device via the network ensuring seamless, real-time data tracking of the physiological and behavioral data of the patient. See at least Para. [0038] – “Some embodiments of the present disclosure provide the following advantages: (1) real time or almost real time monitoring of a patient's physiological data separately or in combination with environmental data for an environment in the vicinity of the patient,” and Para. [0043] – “As described in more detail below, monitoring devices worn by users 140 can monitor a variety of physiological parameters which can be transmitted to monitoring and feedback platform 130 and/or reporting devices ll0A-ll0N for analysis.”)
Regarding claim 7, Deterding does not explicitly disclose The system of claim 1, wherein the monitoring module is configured to track the schedule data, wherein the schedule data comprises at least one of medication dosage, medication administration times, medication name, frequency of medication administration, route of administration, exercise periods, type of exercise, time duration for the exercise, and intensity of the exercise. (See Gellman, at least Col. 3, Lines 59-67 and Col. 4, Lines 1-4 - “The dispensing display 20 may comprise a touch screen that allows for user/patient interface with the dispensing device 10, along with or alternatively to option buttons/input 18. In addition to or alternatively to the display 20, the user or patient may interface with the dispensing device 10 via an application loaded on an external device and/or cloud-based server (see external device 160 and server 162 in FIG. 9) to provide some or all of the interface functionality of display 20/buttons 18. Such functionality includes, but is not limited to: adding new medications to dispense, setting the schedule at which the medications will be dispensed, entering patient information, confirming the dispensing of said medication, etc.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding to utilize the teachings of Gellman since it may assist in tracking adherence to medications (see at least Para. [0040] of Deterding). The Examiner asserts that the particular type of schedule data (i.e., medication dosage, exercise periods, time duration for the exercise, etc.) is simply a label for the schedule data and adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the particular type of data) which does not explicitly alter or impact the steps of the method (i.e., tracking the data ) does not patentably distinguish the claimed invention from the prior art in terms of patentability. Therefore, it would have been obvious to a person of ordinary skill in the art at the time of invention to have the schedule data of Deterding and Gellman include the claimed types of data because the type of reporter data does not functionally alter or relate to the steps of the method and merely labeling the reporter data differently from that of the prior art does not patentably distinguish the claimed invention.
Regarding claim 8, Deterding discloses The system of claim 1, wherein the alert module is further configured to provide one or more alerts and notifications for refiling the medication within the patient monitoring device, wherein the alert module is configured to provide the alerts or reminders in a form of at least one of audios, videos, notifications, and calls for missed medications and upcoming exercise sessions. (See at least Para. [0066] – “These individualized baseline profiles can be compared against the current sensor data and used to generate a health report. Once generated, the monitoring and feedback platform can send the health report to a reporting device (e.g., a mobile phone running an application, a clinical device, etc.) where a caregiver (e.g., parent, medical professional, etc.) can evaluate the data. The health reports may include video of current activity, transmitted using SMS or MMS alerts, and the like.” The Examiner notes that the language “…for refiling the medication…” is a statement of intended use and fails to result in a manipulative difference between the claimed invention and the prior art.”
Regarding claim 9, Deterding partially discloses The system of claim 1, wherein the patient monitoring device comprises an output module that is adapted to transmit the schedule data and the generated insights and predictive analytics to the authorized user and the patient. (See at least Para. [0066] – “These individualized baseline profiles can be compared against the current sensor data and used to generate a health report. Once generated, the monitoring and feedback platform can send the health report to a reporting device (e.g., a mobile phone running an application, a clinical device, etc.) where a caregiver (e.g., parent, medical professional, etc.) can evaluate the data. The health reports may include video of current activity, transmitted using SMS or MMS alerts, and the like.” However, Deterding does not explicitly disclose transmitting schedule data. See Gellman, at least Col. 11, Lines 25-32 – “Some or all data and information including, but not limited to, patient profiles, medication, medication dosage, medication schedules, medication location in dispensing device, etc. may be located in the cloud for easy access by the user through the phone, web, or desktop application. A limited subset of this data may exist on the device for smooth and continuous operation in case of network failure.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding to include schedule data as taught by Gellman since it may assist in tracking adherence to medications (see at least Para. [0040] of Deterding).
Regarding claim 10, Deterding does not explicitly disclose The system of claim 1, wherein the patient monitoring device comprises a plurality of holders that are mounted on both sides of the patient monitoring device, wherein each holder is configured holding at least one medicine, wherein each holder is configured with at least one sensor that is configured for at least one of an inventory control, a dosage verification, and detecting empty or missing the medicine. (In light of the 112 rejection above, Gellman teaches this. See Gellman, Col. 5, Lines 43-58 – “Rotation of the pill dispense gear 126 affects rotation of mating gear 110/108, which rotates the pill capture head to pick up a pill in the capture 45 slot and then keep rotating until the pill falls out from the cap/container assembly 30 and through the pill dispense channel 22 formed through notch 129 in the gear platform 122 (FIG. 2), and gets placed in the pill cup located on the exterior of the device where the user can then take his/her 50 medication. As the pill falls, it passes a sensor 136 (e.g. optical sensor such as an IR light and photodiode shown in FIG. 3 and FIG. 4) to allow for indication of whether a pill is successfully dispensed, as well as tally the number of pills being dispensed. To ensure that the dispensed pill was ingested, camera 20 may take an image or video, and store image/video data in memory 156 or cloud-based server 162 (see FIG. 9).” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding to utilize the teachings of Gellman since it may assist in tracking adherence to medications (see at least Para. [0040] of Deterding).
Regarding claim 11, Deterding does not explicitly disclose The system of claim 1, wherein the monitoring module is configured to capture either video or image data of the patient during medication consumption activity, wherein the captured video or image data is analyzed by the gesture-detection module to detect the abnormality actions that is associated with medication adherence, wherein the abnormality actions are indicative of potential non-adherence behaviors. (See Gellman Col. 5, Lines 51-62 – “As the pill falls, it passes a sensor 136 (e.g. optical sensor such as an IR light and photodiode shown in FIG. 3 and FIG. 4) to allow for indication of whether a pill is successfully dispensed, as well as tally the number of pills being dispensed. To ensure that the dispensed pill was ingested, camera 20 may take an image or video, and store image/video data in memory 156 or cloud-based server 162 (see FIG. 9). Application software 154, which may be implemented locally from memory 156 or externally from cloud-based server 162, may also include face recognition 60 functionality to confirm the specified patient has administered the dose.”
Regarding claim 12, Deterding does not explicitly disclose The system of claim 11, wherein the gesture-detection module is configured to compare the captured video or image data with the schedule data to identify the timing and frequency of medication adherence events to identify the potential medication non-adherence, such as missed doses or potential overdoses, thereby provide the alerts or reminders in a form of at least one of audios, videos, notifications, and calls to the authorized person. (In light of the 112 rejections, Gellman teaches this. See Gellman Col. 5, Lines 51-62 – “As the pill falls, it passes a sensor 136 (e.g. optical sensor such as an IR light and photodiode shown in FIG. 3 and FIG. 4) to allow for indication of whether a pill is successfully dispensed, as well as tally the number of pills being dispensed. To ensure that the dispensed pill was ingested, camera 20 may take an image or video, and store image/video data in memory 156 or cloud-based server 162 (see FIG. 9). Application software 154, which may be implemented locally from memory 156 or externally from cloud-based server 162, may also include face recognition 60 functionality to confirm the specified patient has administered the dose.”, and Col. 9, Lines 18-28 – “Once pill(s) have been dispensed, the user can ingest them or leave them in cup 24 to get water, go to the bathroom, etc. The device 10 may be further programmed remind the user 20 that pills are waiting to be taken, either through a sound or other push notifications or text messages, etc. Once the user removes the pill cup 24 the camera 20 starts recording a video. Video stops after a specified time or when the user places the pill cup back into its location. All pill dispensing events and associated data (e.g. user authentication, pills dispensed into the pill cup, pill cup removal, and the video log) are all logged and stored.)” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding to utilize the teachings of Gellman since it may assist in tracking adherence to medications (see at least Para. [0040] of Deterding).
Claims 13 and 20 feature limitations similar to those of claim 1, and are therefore rejected using the same rationale.
Claim 14 features limitations similar to those of claim 8, and is therefore rejected using the same rationale.
Claim 15 features limitations similar to those of claims 3 and 6, and is therefore rejected using the same rationale.
Claim 17 features limitations similar to those of claim 5, and is therefore rejected using the same rationale.
Claim 19 features limitations similar to those of claim 7, and is therefore rejected using the same rationale.
Claim(s) 4, 16, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Deterding (US 2021/0043321) in view of Gellman (US 11,554,081), and further in view of Valys (US 2019/0076031).
Regarding claim 4, in light of the 112 rejection above, Deterding discloses The system of claim 1, wherein the gesture-detection module is configured to perform predictive analysis to detect the ADLs based on the physiological and behavioral data of the patient,… wherein the physiological and behavioral data of the patient comprises a real-time patient vital sign data, facial expressions, postures, gestures, limb positions, hand positions, reflexes, qualities of a patient’s voice, and intensity. (See at least Para. [0055] – “Physiological information sensed from a patient is sent to a remote server by either a wearable device or a mobile device worn coupled to a user. In some embodiments, a local hub or a router within wireless range from the user can connect to the remote server and transmit the physiological information. After the physiological information is received by the remote server, this information is stored on the server. In some embodiments, this information is first processed by a pre-processing algorithm to eliminate artifacts in the information. In some embodiments, machine learning algorithms are applied on the pre-processed information. Examples of machine learning algorithms can include, but not limited to, feature extraction, patent recognition, and causality analysis. (See FIG. 13 for an example).” The Examiner asserts that the particular type of physiological and behavioral data (i.e., facial expressions, postures, gestures, limb positions, etc.) is simply a label for the schedule data and adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the particular type of data) which does not explicitly alter or impact the steps of the method (i.e., predictive analysis based on the data ) does not patentably distinguish the claimed invention from the prior art in terms of patentability. Therefore, it would have been obvious to a person of ordinary skill in the art at the time of invention to have the physiological and behavioral data of Deterding and Gellman include the claimed types of data because the type of physiological and behavioral data does not functionally alter or relate to the steps of the method and merely labeling the physiological and behavioral data differently from that of the prior art does not patentably distinguish the claimed invention.
Deterding does not explicitly disclose wherein the gesture-detection module is trained with various physiological and behavioral parameters of multiple patients. (See Valys, at least Para. [0028] – “Some embodiments described herein, thus, detect when the observed behavior of the primary sequence of physiological data with respect to the passage of time and/or in response to the observed secondary sequence of data differs from what is expected given the training examples used to train the model. When the training example is gathered from normal individuals or from data that has been previously categorized as normal for a specific user, then the system can serve as an abnormality detector.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Deterding and Gellman to utilize the teachings of Valys since they are in the same field of endeavor (i.e., monitoring of patient behavior), and all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions and the combination would have yielded predictable results to one of ordinary skill in the art at the time of the invention.)
Claims 16 and 18 feature limitations similar to those of claim 4, and are therefore rejected using the same rationale.
Conclusion
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/KYLE G ROBINSON/Examiner, Art Unit 3685
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685