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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.
Status of Claims
The amendments and remarks filed on 25JUL025 have been entered and considered.
Claims 19-38 are currently pending.
No claims have been amended.
Claims 8-14 have been canceled.
Claims 19-28, 30, 33, 35-36, & 38 are subject to restriction by original presentation.
New matter has been added to claims 29, 31-21, 34, & 37.
Priority to the provisional application 63023259 filed on 12MAY2020 has been denied for
similar New Matter issues as detailed below.
Claims 29, 31-32, 34, & 37-38 are under examination.
Election/Restrictions
Newly submitted claims 19-28 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons:
Claims 19-28 are directed to methods unrelated to the originally presented claims.
Originally elected independent claim 9 relates to “A method of using a wellness monitoring system to monitor a daily routine of a first person, measuring one or more health and/or activity metrics”, i.e. monitoring a person’s routine. The withdrawn claims 19-28 are not related to claim 9 for the following reasons: Claim 19 is directed to “A method of determining and improving emotional state of a first person being monitored by a second person”. This is not the routine of the patient, rather just the emotional states. Claims 20-23 are depending from claim 19 and additionally are directed towards uplifting the user’s mood. Claim 24 is directed to “A method of determining morning wake up time and time when the person went to sleep, via a daily monitoring system of a first person”. This is directed toward sleep analysis rather than a routine. Claims 25-28 depend from claim 24 and additionally are directed towards sleep monitoring and tracking a user’s sleep schedule withing certain frequencies. Therefore, claims 19-28 are not related to originally elected claim 9 and its dependent claims.
Claims 30, 33, 35-36, & the scope of claim 38 are further directed to unrelated species from the originally elected claims.
Claim 30 is directed to “implementing the comparison against a cohort different person or others in similar in predetermined groups…. And done in the first device”. This differs from the originally presented claims as there is no mention of comparing against a cohort nor doing the comparisons in the first device. The originally elected independent claim 9 recites making a comparison at the second device. Therefore, claim 30 does not align with the originally elected claims, and has been withdrawn from consideration. Claims 33 & 35 are further withdrawn for depending upon the restricted Claim 30.
Claim 33 is directed to “implement the comparison against a cohort different person or others in similar in predetermined groups” This differs from the originally presented claims as there is no mention of comparing against a cohort. The originally elected independent claim 9 recites making a comparison at the second device. Therefore, claim 33 does not align with the originally elected claims, and has been withdrawn from consideration.
Claim 36 is directed to “the comparing of the data and behavior patterns is provided by the second person, is done in the first person device” This differs from the originally presented claims as there is no mention of doing the comparisons in the first device. The originally elected independent claim 9 recites making a comparison at the second device. Therefore, claim 36 does not align with the originally elected claims, and has been withdrawn from consideration.
Claim 38 is directed to “to determine differences in the historic patterns using first person data or against a cohort person or others in similar in predetermined groups.” This differs from the originally presented claims as there is no mention of comparing against a cohort. The originally elected independent claim 9 recites making a comparison at the second device. Therefore, the scope of claim 38 does not align with the originally elected claims, and this portion of limitations is withdrawn from consideration.
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits. Accordingly, claims 19-28 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
To preserve a right to petition, the reply to this action must distinctly and specifically point out supposed errors in the restriction requirement. Otherwise, the election shall be treated as a final election without traverse. Traversal must be timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are subsequently added, applicant must indicate which of the subsequently added claims are readable upon the elected invention.
Should applicant traverse on the ground that the inventions are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other invention.
Response to Arguments
Applicant's amendments filed 25JUL2025 regarding the rejections of claims 8-14 under 35 U.S.C 101 have been fully considered and obviate the rejection. Therefore, the rejections have been withdrawn. Applicant has not provided arguments pertaining to the 101 rejections. Further rejection of newly added claims 29-38 are provided below.
Applicant's amendments filed 25JUL2025 regarding the rejections of claims 8-14 under 35 U.S.C 103 have been fully considered and obviate the rejection. Therefore, the rejections have been withdrawn. Applicant has not provided arguments pertaining to the 103 rejections. Further rejection of newly added claims 29-38 are provided below.
Claim Objections
Claims 29, 32, & 37 are objected to because of the following informalities:
Regarding claim 29:
The claim recites “method of using a historic data pattern matching” in Line 1. This should instead be “method of using
The claim recites “collecting historical set of data” in Line 16. This should instead be “collecting a historical set of data” to be grammatically correct.
The claim recites “of the first person at first device” in Line 17. This should instead be “of the first person at the first device” to be grammatically correct.
The claim recites “and behavior multiple data patterns” in Line 18. This should instead be “and behavior of multiple data patterns” to be grammatically correct.
The claim recites “or changing configuring a threshold for one or more given historic patterns” in Line 31. This should instead be “or changing the configuration of a threshold for one or more given historic patterns” to be grammatically correct.
Regarding claim 32:
The claim recites “calculate the trending data is calculated” in Line 3. This should instead be “calculate the trending data is calculated” to be grammatically correct.
Regarding claim 37:
The claim recites “second person, is done in” in Line 2. This should instead be “second person, and is done in” to be grammatically correct.
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 29, 31-32, 34, & 37-38 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.
Regarding Claim 29:
The claim recites “A method of using a historic data pattern matching to detect abnormal or unusual behavior patterns for a routine of a first person to be monitored by a second person” in Lines 1-2. There is no support found for the portion “historic data pattern matching” in the Specification. No portion of the Specification appears to discuss historic data pattern matching. Therefore, the claim does not have a written description and lacks support.
The claim recites “pattern matching wellness monitoring system” in Line 4. There is no support found in the Specification. No portion of the Specification appears to discuss a pattern matching wellness monitoring system. Therefore, the claim does not have a written description and lacks support.
The claim recites “review and/or analyze the set of historic pattern matching unusual or abnormal data stored at the system cloud server” in Lines 14-15. There is no support found in the Specification. No portion of the Specification appears to discuss a reviewing and/or analyzing the set of historic pattern matching unusual or abnormal data stored at the system cloud server. ¶0005 of the Specification states the review of data at the second device, but there is no mention of this analysis at the system cloud server. Therefore, the claim does not have a written description and lacks support.
The claim recites “the behavior multiple data patterns of the first person at first device” in Lines 16-17. There is no support found in the Specification. No portion of the Specification appears to discuss a behavior multiple data patterns. Therefore, the claim does not have a written description and lacks support.
The claim recites “comparing the collected historical set of data and behavior multiple data patterns, inside the first device” in Lines 18-19. There is no support found in the Specification. No portion of the Specification appears to discuss comparing the collected historical set of data and behavior multiple data patterns, inside the first device. ¶0039 of the specification discusses a second device stating ‘“In an embodiment of the present disclosure, the second device 212 is configured to review, analyze, and compare, the set of data stored at the system cloud server 210.”. Additionally, this can be seen in ¶0048 showing the second device rather than the first. Therefore, the claim does not have a written description and lacks support.
The claim recites “determining the abnormal or unusual pattern, wherein the predetermined threshold is set by one of the first person or the second person” in Lines 19-20 . There is no support found in the Specification. No portion of the Specification appears to discuss a determining the abnormal or unusual pattern, wherein the predetermined threshold is set by one of the first person or the second person. The opposite can be found in ¶0012 of the specification stating ““The wellness monitoring system extracts abnormal or unusual pattern of the first person based on a predetermined threshold set by comparing the historic data and the set of data received on daily basis.”. This contradiction is also found in ¶0054. Therefore, the claim does not have a written description and lacks support.
Claims 31-32, 34, & 37-38 are additionally rejected for depending upon the rejected claim 29.
Regarding Claims 31-32:
The claim recites “a rate of change of the data over time” in Line 3. There is no support found in the Specification. No portion of the Specification appears to discuss a rate of change of the data over time. Therefore, the claim does not have a written description and lacks support.
The claim recites “display this this rate of change of data via the first device” in Line 4. There is no support found in the Specification. No portion of the Specification appears to discuss display this this rate of change of data via the first device. The specification states that the data is displayed to the second device, rather than the first device, Therefore, the claim does not have a written description and lacks support.
Claims 32 & 37 are additionally rejected for depending upon the rejected claim 31.
Regarding Claims 34 & 37:
The claim recites “comparing is done in the cloud server to determine the abnormal or unusual pattern” in Line 1. There is no support found in the Specification. No portion of the Specification appears to discuss where comparing is done in the cloud server to determine the abnormal or unusual pattern. The Specification is found to disclose the opposite of this limitation in ¶0005 stating “wherein the second device is configured to review, analyze, and compare, the set of data stored at the system cloud server.”, as well as ¶0039. Therefore, the claim does not have a written description and lacks support.
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 29, 31-32, 34, & 37-38 are 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 29:
The limitation “wherein the first device comprises a routine daily or routinely monitoring application” in line 10 is unclear if this is intended to recite a device that tracks daily routines or one that is routinely monitoring a patient. For the purpose of examination, the examiner is interpreting this as a device that tracks a patient’s routine.
The limitation “review and/or analyze the set of historic pattern matching unusual or abnormal data” in lines 14-15 is unclear how the device can analyze historic data that hasn’t been collected in the system yet. It is not clear where or what this historic data is therefore referring to. For the purpose of examination, the examiner is interpreting this as reviewing baseline data for a patient to determine abnormal activity.
The limitation “collecting historical set of data,” in line 16 is unclear how the device can collect historic data, since the data isn’t historic if it is being generated in real time. For the purpose of examination, the examiner is interpreting this as reviewing baseline data saved in the system.
The limitation “comparing the collected historical set of data and behavior multiple data patterns ,inside the first device, with current multiple data patterns” in lines 18-19 is unclear what current data patterns is referring to since a current data pattern has not been established to be collected by the system yet, only historical data. For the purpose of examination, the examiner is interpreting this as collecting data which is compared to a pre-known patient baseline.
The limitation “displaying the set of and/or for” in line 26-27 is unclear if this is intending to display data sets or something else that is missing from the limitation. For the purpose of examination, the examiner is interpreting this as displaying of data.
The limitation “Communication to send to the second device for presenting to the first person data ” in lines 23-24 is unclear how this presents to the first person if the first user controls the first device and another has the second device. For the purpose of examination, the examiner is interpreting this as the communication regarding the first user is sent to the second device for review.
Claim 29 recites the limitation " the set of historic pattern matching unusual or abnormal data" in Lines 14-15. There is insufficient antecedent basis for this limitation in the claim.
Claim 29 recites the limitation "wherein the predetermined threshold " in Lines 20-21. There is insufficient antecedent basis for this limitation in the claim.
Claim 29 recites the limitation "pattern detection" in Line 22. There is insufficient antecedent basis for this limitation in the claim.
Claim 29 recites the limitation "alert " in Line 22. There is insufficient antecedent basis for this limitation in the claim.
Claim 29 recites the limitation " receiving the communication at the second computing device " in Line 26. There is insufficient antecedent basis for this limitation in the claim.
Claims 31-32, 34, & 37-38 are further rejected for depending upon rejected claim 29.
Regarding claim 31:
Claim 31 recites the limitation " A method of Claim 29" in Line 1. There is insufficient antecedent basis for this limitation in the claim.
Claim 31 recites the limitation " the trending data" in Line 3. There is insufficient antecedent basis for this limitation in the claim.
Claims 32 & 37 are further rejected for depending upon the rejected claim 31.
Regarding claim 32:
The limitation “calculate the trending data is calculated, which is rate of change of the data over time; and display this this rate of change of data via the second device” in line 3 is unclear if this is the same data for both devices or a new data set for the second device. For the purpose of examination, the examiner is interpreting this as the same data.
Claim 31 recites the limitation " A method of Claim 31, " in line 1. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 34:
Claim 34 recites the limitation " A method of Claim 29" in Line 1. There is insufficient antecedent basis for this limitation in the claim.
The limitation “wherein the comparing is done in the cloud server to determine the abnormal or unusual pattern” in lines 1-2 is unclear how the comparisons are done in the cloud server when claim 29 has already established that the comparisons are completed in the first device. For the purpose of examination, the examiner is interpreting this as the comparisons are done through the shared communication system which connects the cloud to both devices.
Claim 34 recites the limitation " A method of Claim 30" in Line 1. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 37:
Claim 37 recites the limitation " A method of Claim 32" in Line 1. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 38:
Claim 38 recites the limitation " wherein the pattern matching wellness monitoring system " in Line 1. There is insufficient antecedent basis for this limitation in the claim.
The limitation “a cohort different person or others in similar in predetermined groups,” in lines 3-4 is unclear if this means a predetermined group of people from a similar cohort or of that of a different cohort, or something else. For the purpose of examination, the examiner is interpreting this as people who share demographic information with the patient.
Claim 38 recites the limitation " other statistical or machine learning or neural network techniques " in Line 2. There is insufficient antecedent basis for this limitation in the claim.
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.
Claims 29, 31-32, 34, & 37-38 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. MPEP 2106(III) outlines steps for determining whether a claim is directed to statutory subject matter. The stepwise analysis for the instant claim is provided here.
Step 1 – Statutory categories
Claim 29 is directed to a method and thus meets the step 1 requirements.
Step 2A – Prong 1
Regarding claim 29, the following step is an abstract idea: “comparing the collected historical set of data and behavior multiple data patterns, inside the first device, with current multiple data patterns using a threshold or mathematical formula for change”, and “determining the abnormal or unusual pattern,” ; which are mental processes when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(II), the mental process grouping includes observations, evaluations, judgements, and opinions. In this case, a human could collect/analyze baseline data and physiological data to determine an illness risk metric, such as a human doctor evaluating data and providing a diagnosis, and then displaying it on a secondary device such as adding the results to a shared computer system.
Step 2A – Prong 2
Regarding claim 29, the abstract idea is not integrated into a practical application.
The following claim elements do not add any meaningful limitation to the abstract idea: “pattern matching wellness monitoring system”, “one or more processors”; “a memory coupled to the one or more processors”; “a first device configured to be handled by the first person”; “a system cloud server”; “collect a set of data associated with the first person, “; “communication network”; “wherein the system cloud server collects and stores the data “; “second device associated with the second person “; “collecting historical set of data, at a predetermined frequency, about the behavior multiple data patterns of the first person at first device”; “the second device is configured to review and/or analyze the set of historic pattern matching unusual or abnormal data stored at the system cloud serve” “sending the abnormal or unusual pattern detection or alert to the second device”; generating, at the system cloud server, a communication to send to the second device for presenting to the first person data and/or alerting the second person of the abnormal pattern; “receiving the communication at the second computing device and displaying the set of and/or for alerting the second person of the abnormal pattern of the first person via the second device”; and “wherein, based on the displayed data or abnormal pattern, the second device is configured for interaction by the second person to adjust or correct the abnormal pattern or changing configuring a threshold for one or more given historic patterns to trigger desired notifications”.
The communication network; pattern matching wellness monitoring system; first device; second device; processors; memory are recited at a high level of generality that amount to generic computer components for implementing the abstract idea.
The limitations of “collect a set of data associated with the first person,” is data that is necessary to implement the abstract idea on a computer or perform the methods.
The limitations of “wherein the system cloud server Is connected with the first device and the second device through a communication network, and wherein the system cloud server collects and stores the data”, “the second device is configured to review and/or analyze the set of historic pattern matching unusual or abnormal data stored at the system cloud serve”; “collecting historical set of data, at a predetermined frequency, about the behavior multiple data patterns of the first person at first device;”; “wherein the predetermined threshold is set by one of the first person or the second person “ and “communicating, to the second device by the system cloud server, the set data for the first person” are data gathering steps, which amount to no more than insignificant extra-solution activity.
The step of “sending the abnormal or unusual pattern detection or alert to the second device”; generating, at the system cloud server, a communication to send to the second device for presenting to the first person data and/or alerting the second person of the abnormal pattern; “receiving the communication at the second computing device and displaying the set of and/or for alerting the second person of the abnormal pattern of the first person via the second device”; “wherein, based on the displayed data or abnormal pattern, the second device is configured for interaction by the second person to adjust or correct the abnormal pattern or changing configuring a threshold for one or more given historic patterns to trigger desired notifications” amounts to no more than insignificant extra-solution activity of data display.
Step 2B
Regarding claim 29, the abstract idea does not amount to significantly more than the abstract idea itself.
The following claim elements do not add any meaningful limitation to the abstract idea:
The following claim elements do not add any meaningful limitation to the abstract idea: “pattern matching wellness monitoring system”, “one or more processors”; “a memory coupled to the one or more processors”; “a first device configured to be handled by the first person”; “a system cloud server”; “collect a set of data associated with the first person, “; “communication network”; “wherein the system cloud server collects and stores the data “; “second device associated with the second person “; “collecting historical set of data, at a predetermined frequency, about the behavior multiple data patterns of the first person at first device”; “the second device is configured to review and/or analyze the set of historic pattern matching unusual or abnormal data stored at the system cloud serve” “sending the abnormal or unusual pattern detection or alert to the second device”; generating, at the system cloud server, a communication to send to the second device for presenting to the first person data and/or alerting the second person of the abnormal pattern; “receiving the communication at the second computing device and displaying the set of and/or for alerting the second person of the abnormal pattern of the first person via the second device”; and “wherein, based on the displayed data or abnormal pattern, the second device is configured for interaction by the second person to adjust or correct the abnormal pattern or changing configuring a threshold for one or more given historic patterns to trigger desired notifications”. None of the above features amounts to more than what is well-understood, routine, and conventional.
Dependent claims 30-38 do not integrate the abstract idea into a practical application and do not add significantly more to the abstract idea of claim 29. The dependent claim limitations are directed to defining Data types (Claims 34 & 37-38 ), data analysis (Claims 31-32), and displaying results or information (Claims 31-32) which are insignificant extra-solution activity. None of the above features amounts to more than what is well-understood, routine, and conventional.
In summary, claims 29, 31-32, 34, & 37-38 are directed to an abstract idea without significantly more and, therefore, are patent ineligible.
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 –
Claims 29, 31-32, 34, & 37-38 are rejected under pre-AIA 35 U.S.C. 102(a)(1) as being anticipated by Kalantarian et al. (US Publication No. 20210275023; Previously Cited).
Regarding claim 29, Kalantarian discloses a method of using a historic data pattern matching to detect abnormal or unusual behavior patterns for a routine of a first person (Kalantarian Claim 1 “real time and historic visualizations and analysis of the health, behavior, lifestyle, and safety of said individual can be viewed, which comprise a multitude of the following: stress detection, device adherence detection, location, fall detection, physical activity detection, daily step totals, heart rate, weather hazard detection, indoor temperature detection, and sleep tracking”); to be monitored by a second person (Kalantarian ¶0028 “An example embodiment of the caregiver dashboard 115 is shown in FIG. 3. While the dashboard could take many forms, primarily it is the software running on a device used by the caregiver 135 that functions as the primary gateway to receive updates, alerts, and notifications about the well-being of the patient 100.”), wherein method comprises: providing a pattern matching wellness monitoring system (Kalantarian ¶0081) comprising: one or more processors (Kalantarian ¶0027 “one or more general purpose hardware processors programmed to perform the techniques pursuant to program instructions in firmware”); a memory coupled to the one or more processors (Kalantarian ¶0027);a first device configured to be handled by the first person (Kalantarian ¶0006 “The system consists of a mobile/wearable device which collects and calculates a variety of health, safety, and wellness data such as their location, environment, fitness levels, heart rate, sleep quality, current activity, if they have fallen, stress levels, behavioral trends, and more.”); a system cloud server (Kalantarian ¶0081 “These two parameters are combined into a single Stress Score with a coefficient configurable from the cloud based on their unique understanding of the patient's expected pattern of behavior.”); and a second device associated with the second person Kalantarian ¶0028 “An example embodiment of the caregiver dashboard 115 is shown in FIG. 3. While the dashboard could take many forms, primarily it is the software running on a device used by the caregiver 135 that functions as the primary gateway to receive updates, alerts, and notifications about the well-being of the patient 100.”), wherein the first device comprises a routine daily or routinely monitoring application configured to collect a set of data associated with the first person (Kalantarian ¶0082 “The system represents a framework to holistically profile an individual's wellness including stress, sleep quality, fitness, and longitudinal lifestyle changes.”), wherein the system cloud server is connected with the first device and the second device via a communication network (Kalantarian ¶0024-¶0025), and wherein the system cloud server collects and stores the data (Kalantarian ¶0056 “Data from all these modules is periodically stored in the database 925, for subsequent analysis.”), and wherein the second device is configured to review and/or analyze the set of historic pattern matching unusual or abnormal data stored at the system cloud server (Kalantarian ¶0075 “The Machine Learning Subsystem therefore presents a flexible, scalable approach to identify and track various mental and physiological disorders through the patient's behavior, physiological data, interaction with their mobile/wearable device 105.”); collecting historical set of data, at a predetermined frequency, about the behavior multiple data patterns of the first person at first device (Kalantarian ¶0056 “The stress score subsystem runs on the Patient device 105 in this embodiment and counts the number of transitions reported by the Activity Recognition 905 module between an active state (e.g. walking) and inactive state (e.g. idle). When a transition occurs between these two states, a software counter is incremented on the patient device and the number of transitions per hour is updated 910.”), comparing the collected historical set of data and behavior multiple data patterns ,inside the first device, with current multiple data patterns using a threshold or mathematical formula for changes, and determining the abnormal or unusual pattern, wherein the predetermined threshold is set by one of the first person or the second person (Kalantarian ¶0044“Some embodiments may buffer the accelerometer data in memory before they are processed by the motion detector block. If the embodiment includes an accelerometer, the intensity of the three-dimensional accelerometer (x, y, z) reading could be calculated…which would be compared to a threshold 602 to determine if the motion is significant enough to indicate a fall (an intensity higher than the threshold would indicate a fall). The threshold value 602 is customizable from the server 110, as caregivers or patients may desire to increase or decrease their fall sensitivity settings to manage the tradeoffs between true positives and false negatives.”; 0077 “The details of the method in which the Classification/Regression module is trained are standard practice in the field, and are based on the behavioral data as well as the associated health data 1120 manually entered by the user that functions as a gold standard for the accuracy of the device.”) sending the abnormal or unusual pattern detection or alert to the second device; generating, at the system cloud server, a communication to send to the second device for presenting to the first person data and/or alerting the second person of the abnormal pattern; receiving the communication at the second computing device and displaying the set of and/or for alerting the second person of the abnormal pattern of the first person via the second device (Kalantarian ¶0006 “The system consists of a mobile/wearable device which collects and calculates a variety of health, safety, and wellness data such as their location, environment, fitness levels, heart rate, sleep quality, current activity, if they have fallen, stress levels, behavioral trends, and more. This information is processed and transmitted to a caregiver, who can view and visualize the data and receive real-time notification of potential hazards.”); wherein, based on the displayed data or abnormal pattern, the second device is configured for interaction by the second person to adjust or correct the abnormal pattern or changing configuring a threshold for one or more given historic patterns to trigger desired notifications (Kalantarian ¶0029 “ Moreover, this is the interface through which the caregiver can select the sensitivity of the motion detector 605 to be described hereafter in the Fall Detection module. Additional settings and customizations are also housed within the settings page.”).
Regarding claim 31, Kalantarian further discloses wherein the pattern matching wellness monitoring system is configured to: calculate the trending data, which is a rate of change of the data over time (Kalantarian ¶0057 “Similarly, the Transitions Per Hour 915 block following the Activity Recognition subsystem 905 could report that the patient has changed between idle and active states at a rate four times greater than the historic average and the screen has turned on/off at a rate that is average. In this embodiment, the stress score from each module would be weighed equally and averaged using”); and display this this rate of change of data via the first device (Kalantarian ¶0026 “Additional on-device logic to filter, smooth, and process acquired sensor data could run on the microprocessor 250 and optionally be displayed on the device display 245 similar to a smartwatch.”).
Regarding claim 32, Kalantarian further discloses wherein the pattern matching wellness monitoring system is configured to: calculate the trending data is calculated, which is rate of change of the data over time (Kalantarian ¶0057 “Similarly, the Transitions Per Hour 915 block following the Activity Recognition subsystem 905 could report that the patient has changed between idle and active states at a rate four times greater than the historic average and the screen has turned on/off at a rate that is average. In this embodiment, the stress score from each module would be weighed equally and averaged using”);and display this this rate of change of data via the second device (Kalantarian ¶0057 “As this stress score likely exceeds the baseline of 1, the caregiver dashboard would be updated accordingly indicating a high level of stress in the recent epoch.”).
Regarding claim 34, Kalantarian further discloses wherein the comparing is done in the cloud server to determine the abnormal or unusual pattern (Kalantarian ¶0067 “The Machine Learning subsystem is a flexible framework for screening and tracking of various physiological and mental health disorders using the foregoing sensing modalities. One embodiment of this system is shown in FIG. 11. During initial setup and account registration, patient demographic information and health data 1120 are saved to the database on the server 110. “; ¶0075 “The Machine Learning Subsystem therefore presents a flexible, scalable approach to identify and track various mental and physiological disorders through the patient's behavior, physiological data, interaction with their mobile/wearable device 105.”).
Regarding claim 37, Kalantarian further discloses wherein the comparing of the data and behavior patterns is provided by the second person, is done in the cloud server to determine the abnormal or unusual pattern (Kalantarian ¶0067 “The Machine Learning subsystem is a flexible framework for screening and tracking of various physiological and mental health disorders using the foregoing sensing modalities. One embodiment of this system is shown in FIG. 11. During initial setup and account registration, patient demographic information and health data 1120 are saved to the database on the server 110. “; ¶0075 “The Machine Learning Subsystem therefore presents a flexible, scalable approach to identify and track various mental and physiological disorders through the patient's behavior, physiological data, interaction with their mobile/wearable device 105.”).
Regarding claim 38, Kalantarian further discloses wherein the pattern matching wellness monitoring system is configured to use other statistical or machine learning or neural network techniques to determine differences in the historic patterns (Kalantarian ¶0067 “The Machine Learning subsystem is a flexible framework for screening and tracking of various physiological and mental health disorders using the foregoing sensing modalities. One embodiment of this system is shown in FIG. 11. During initial setup and account registration, patient demographic information and health data 1120 are saved to the database on the server 110. “; ¶0075 “The Machine Learning Subsystem therefore presents a flexible, scalable approach to identify and track various mental and physiological disorders through the patient's behavior, physiological data, interaction with their mobile/wearable device 105.”).
Conclusion
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/MEGAN T FEDORKY/Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/Supervisory Patent Examiner, Art Unit 3796