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 1-19 objected to because of the following informalities: the claims use the British-English spellings “behavioural”, “personalise”, “digitise,” and “maximise,” etc. They should be corrected to American-English spelling conventions. Appropriate correction is required.
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.
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim is directed to a computer readable medium, which broadly interpreted includes signal per se. Applicant may correct this rejection by adding “non-transitory” to computer readable medium to disavow signal per se.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-7, 9-16, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vaughan (U.S. Patent Application Publication No. 2019/0043610) hereinafter referred to as Vaughan; in view of Cox (U.S. Patent Application publication No. 2017/0235895) hereinafter referred to as Cox; in view of Tymoszczuk (U.S. Patent Application Publication No. 2016/0023099) hereinafter referred to as Tymoszczuk; in view of Brown et al. (U.S. Patent Application Publication No. 2016/0030834) hereinafter referred to as Brown.
Regarding claim 1, Vaughan teaches a computational personalized cognitive therapeutic system (¶[0012]) comprising one or more processors (¶[0014]) and one or more associated memories (¶[0080]) configured to implement:
a patient clinical database (¶[0084]) comprising a data acquisition interface configured to receive and store input data (¶[0109] data inputs) for a plurality of patients (¶[0109] subject population) from a plurality of heterogeneous data sources (¶[0109] data inputs, Fig. 4 elements 501, 505, 510), the input data for a patient comprising: wearable data (¶[0063] wearable digital monitor) comprising behavioral data and physiological data (¶[0063]), wherein the input data sources for a patient comprise one or more wearable devices (¶[0063]) and a digitized caregiver record (¶[0062]),
a data aggregation and pre-processing module (Fig. 6) configured to pre-process the input data (¶[0114] pre-processing module) in the patient clinical database and generate a patient profile for each patient (¶[0084]);
a digital cognitive therapy delivery module (¶[0085]) configured to deliver a plurality of therapies according to a personalized cognitive digital therapy model to a patient using one or more computing devices (¶¶[0092-0094]), each therapy having a different mechanism of action (MOA) (¶[0086]) and comprising a plurality of adjustable parameters (¶[0177] therapy is adjustable), and the digital cognitive therapy delivery module is further configured to collect a plurality of digital cognitive biomarkers for each therapy (¶[0177], Fig. 2-3), a plurality of behavioral and physiological biomarkers from one or more wearable devices (¶[0063], Fig. 2-3) and/or the one or more computing devices, and to measure interactions of the patient with the digital cognitive therapy delivery module (¶[0177], Fig. 2-3), wherein the plurality of therapies comprises at least a cognitive stimulation game therapy (¶[0151]), a guided learning therapy (¶[0101]);
a cognitive analytics engine configured to process the patient profile, digital cognitive biomarkers, and the behavioral and physiological biomarkers (Fig. 11) using an ensemble of population-based and personalized prediction models (¶[0120]) trained using a plurality of Artificial Intelligence (AI) and Machine Learning (ML) methods (¶[0075]), and which is configured to generate a plurality of metrics to characterize a current cognitive state of the patient (¶[0084], ¶[0109]) and estimate the potential future improvement comprising the probability and size of an expected effect (¶[0110]), wherein the plurality of metrics are generated on demand or at least once per day (¶[0067]); and
a personalized cognitive platform configured to use the plurality of metrics to personalize the personalized cognitive digital therapy model for each patient by adjusting one or more of the plurality of parameters for one or more of the plurality of therapies to maximize the estimated effect level (¶[0060] improve efficacy, ¶[0173] and ¶[0191]), and to use the metrics to generate one or more alerts if a therapy does not meet an expected threshold effect level or a side effect exceeds a threshold side effect level to enable adjustment of a medication by a clinician (¶[0083], ¶[0175] alerted to significant deviations from the….therapies suggested by the therapeutic module),
wherein the system iteratively refines the personalized cognitive digital therapy model for each patient over time by selecting specific therapies from the plurality of therapies and adjusting the associated adjustable parameters, and obtaining an estimate effect of the adjustments, and after delivery of an adjusted treatment by the digital cognitive therapy delivery module, the cognitive analytics engine generates the plurality of metrics to assess actual effects compared to estimated effects in order to further refine the personalized cognitive digital therapy model by the personalized cognitive platform (Fig. 2-4, ¶[0023], and ¶[0173], ¶[0177]).
Vaughan does not teach that the input data includes personal particular and sociodemographic data; patient medical history and background health data; medication data; clinical data; therapies including a reminiscence therapy and a physical and mental wellness therapy;
Attention is brought to the Cox reference, which teaches that the input data includes personal particular and sociodemographic data (¶[0046]); patient medical history (¶[0046]) and background health data (¶[0046] pre-established); medication data (¶[0174]); and clinical data (¶[00174]).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify the cognitive assessment and therapy system of Vaughan to include the additional data sources of Cox, because Cox teaches improved data processing for determination of patient characteristics corresponding to chronic medical conditions (Cox ¶¶[0001-0002]).
Vaughan as modified does not teach therapies including a reminiscence therapy and a physical and mental wellness therapy.
Attention is drawn to the Tymoszczuk reference, which teaches digital cognitive therapies including a reminiscence therapy (¶[0049], ¶[0073])
It would have been obvious to one of ordinary skill in the art to modify the therapies of Vaughan as modified to include additional modalities, because Brown teaches that additional modes of therapy optimize therapy (Tymoszczuk ¶[0038])
Vaughan as modified does not teach a physical and mental wellness therapy.
Attention is drawn to the Brown reference, which teaches a physical and mental wellness therapy (¶[0167]).
It would have been obvious to one of ordinary skill in the art to modify the therapies of Vaughan as modified to include additional modalities, because Brown teaches that additional modes of therapy aid wellbeing and improve neuronal redevelopment associated with robust play (Brown ¶[0254])
Regarding claim 2, Vaughan as modified teaches the system as claimed in claim 1.
Vaughan further teaches wherein the data aggregation and pre-processing module is configured to perform data cleaning, dimensionality reduction and data transformation to prepare the input data for further analysis and use by the cognitive analytics engine (¶[0116]).
Regarding claim 3, Vaughan as modified teaches the system as claimed in claim 1.
Vaughan further teaches wherein: the plurality of digital cognitive biomarkers for the cognitive stimulation game therapy comprises one or more of a game specific performance, finger tapping and finger movement related biomarkers (¶[0063]), reaction time between a stimulus exposure and a response (¶[0106]);
the plurality of digital cognitive biomarkers for the guided learning therapy comprises one or more of a quiz result, an answer confidence, a speed of information processing of content, or a time spent with content (¶[0093], ¶[0106], ¶[0209]); and
digital cognitive biomarkers comprising one or more of a language marker derived from textual analysis or audio analysis, a speech characteristic derived from audio data of the patient (¶[0106]).
Vaughan as modified does not teach the reminiscence therapy or physical and mental wellness therapy.
Tymoszczuk further teaches a plurality of digital cognitive biomarkers for the reminiscence therapy (¶¶[0108-0127]).
It would have been obvious to one of ordinary skill in the art to modify the therapies of Vaughan as modified to include additional modalities, because Brown teaches that additional modes of therapy optimize therapy (Tymoszczuk ¶[0038])
Vaughan as modified does not teach physical and mental wellness therapy.
Brown further teaches a plurality of digital cognitive biomarkers (¶¶[0379-0380]) for the physical and mental wellness therapy comprises one or more of an emotional expression capture indicating a level of enjoyment (¶[0312], ¶[0399]).
It would have been obvious to one of ordinary skill in the art to modify the therapies of Vaughan as modified to include additional modalities, because Brown teaches that additional modes of therapy aid wellbeing and improve neuronal redevelopment associated with robust play (Brown ¶[0254])
Regarding claim 4, Vaughan as modified teaches the system as claimed in claim 1.
Vaughan further teaches wherein the plurality of behavioral and physiological biomarkers comprise one or more of an movement biomarker obtained from an accelerometer and/or a gyroscope (¶[0106]), and an eye tracking biomarker (¶[0106]).
Regarding claim 5, Vaughan as modified teaches the system as claimed in any one of claim 1.
Vaughan further teaches wherein the plurality of metrics comprise: a cognitive baseline pointer (¶[0110]) which is an estimate of a change in the cognitive state of the patient with respect to a baseline generated using the patient profile and an expected behavior effect on the patient generated by the cognitive analytics engine (¶[0110], ¶[0176]);
a mechanism of action pointer for each of the plurality of mechanisms of action which estimates an effect level with respect to an expected effect level for the associated therapy generated by the cognitive analytics engine (¶[0135]);
an average mechanism of action pointer which estimates an average effect of the plurality of therapies with respect to an estimate effect generated by the cognitive analytics engine (¶[0137]); and
a side effects pointer which measures a severity of one or more side effects (¶[0012]).
Regarding claim 6, Vaughan as modified teaches the system as claimed in claim 5.
Vaughan further teaches wherein the personalized cognitive platform comprises a MOA management module, an educational content management module (¶[0177]) and a medication/dose management module (¶[0186]), wherein the MOA management module uses at least the mechanism of action pointers and the average mechanism of action pointer to adjust one or more of the plurality of parameters for one or more of the plurality of therapies and to adjust the dosage of each of the plurality of therapies to maximize the estimated effect level of a therapy (¶[0106], ¶[0173], Figs. 2-4), and wherein the content education module is configured to adjust a digital content provided to a patient based on the patient's interaction behavior measured by the digital cognitive therapy delivery module (¶[0106], ¶[0173]), and the medication/dose management module is configured to record clinical data including medication and dosages and to generate suggested changes to medication and dosages using at least the side effects pointer and the cognitive baseline pointer (¶[0185], Fig. 16).
Regarding claim 7, Vaughan as modified teaches the system as claimed in claim 6.
Vaughan further teaches, wherein the MOA management module is configured to adjust the cognitive stimulation game therapy by adjusting one or more game parameters, game dosage and game timing (¶[0077-0078]), and is configured to adjust the guided learning therapy by adjusting the learn amount and timing, and learning content (¶¶[0093-0094]).
Tymoszczuk further teaches adjusting the reminiscence therapy by adjusting the timing of content, content topics and stimulus (Fig. 4A, ¶[0041], ¶[0038]).
Brown further teaches adjusting the physical and mental wellness therapy by adjusting a modality, an intensity and a duration of physical exercise or mental exercise (¶[0247], ¶¶[0285-0289]).
Regarding claim 9, Vaughan as modified teaches the system as claimed in claim 1.
Vaughan further teaches wherein the system comprises a cloud computing platform (¶[0156]) and the digital cognitive therapy delivery module is configured to execute on one or more patient mobile computing devices (¶[0160]).
Regarding claims 10-17/19, the claims are directed to a method comprising substantially the same subject matter as claims 1-9/1 and are rejected under substantially the same sections of Vaughan and Cox.
Regarding claim 18, Vaughan as modified teaches the method as claimed in claim 10.
Vaughan further teaches wherein the method is implemented using a cloud computing platform (¶[0156]) and the digital cognitive therapy delivery module is configured to execute on one or more patient mobile computing devices (¶[0160]).
Claim(s) 8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vaughan, Cox, Tymoszczuk, and Brown as applied to claims 1 and 10 above, and further in view of Hernandez (U.S. Patent Application Publication No. 2020/0082927) hereinafter referred to as Hernandez.
Regarding claim 8, Vaughan as modified teaches the system as claimed in claim 1.
Vaughan further teaches wherein the digital cognitive therapy delivery module provides a user interface on a computing device (¶[0114]) comprising:
a medication schedule module configured to record a medication schedule and track compliance (¶[0023], ¶[0060], ¶[0110]); and
a therapy module configured to provide the plurality of therapies to the patient (Figs. 2-4.
Vaughan as modified does not teach a reminder and calendar module configured to allow patients to record reminders and to notify the patient of a scheduled therapy, and monitors therapy compliance; a note module configured to track goals and record electronic information to assist with daily living activities; an electronic gratitude journal; a mood tracker configured to estimate and/or record a mood of a patient, and to provide feedback on past mood history and to provide mood data to a clinician and/or the cognitive analytics engine; a social media module to facilitate communication with family, friends and support groups; a gamification system which awards points for completion of therapy or tasks, and rewards for achieving specific points goals, and a comparative score based on treatment progress with respect to other patients with similar diagnosis; a diet tracking module configured to collect consumption data and provide dietary recommendations; and a therapy module configured to provide the plurality of therapies to the patient.
Attention is brought to the Cox reference, which teaches a reminder (¶[0060]) and calendar module configured to allow patients to record reminders and to notify the patient of a scheduled therapy (¶[0060]), and monitors therapy compliance (¶[0171]);
a note module configured to track goals and record electronic information to assist with daily living activities (¶[0052], ¶[0057], ¶[0067]); and
a diet tracking module configured to collect consumption data and provide dietary recommendations (¶[0117], ¶[0056]).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify the assessment system of Vaughan as modified to include additional patient interface modules, as taught by Cox, because they optimize the system for monitoring patient compliance to a treatment plan (Cox ¶[0070]).
Vaughan as modified does not teach an electronic gratitude journal; a mood tracker configured to estimate and/or record a mood of a patient, and to provide feedback on past mood history and to provide mood data to a clinician and/or the cognitive analytics engine; a social media module to facilitate communication with family, friends and support groups; a gamification system which awards points for completion of therapy or tasks, and rewards for achieving specific points goals, and a comparative score based on treatment progress with respect to other patients with similar diagnosis.
Attention is drawn to the Tymoszczuk reference, which teaches a mood tracker configured to estimate and/or record a mood of a patient, and to provide feedback on past mood history and to provide mood data to a clinician and/or the cognitive analytics engine (¶¶[0128-0134]);
a social media module to facilitate communication with family, friends and support groups (¶¶[0011-0012]);
a gamification system which awards points for completion of therapy or tasks (¶[0062]), and rewards for achieving specific points goals, and a comparative score based on treatment progress (¶[0076]) with respect to other patients with similar diagnosis (¶[0078] omniscient view of the data as a community).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify the cognitive therapy system of Vaughan as modified to include additional social media, mood, and gamification systems as taught by Tymoszczuk because Tymoszczuk teaches determining the relationships between brain and body in order to optimize outcomes (Tymoszczuk ¶[0008]).
Vaughan as modified does not teach a gratitude journal.
Attention is brought to the Hernandez reference, which teaches a gratitude journal (¶[0226], ¶[0230], Fig. 5A-B).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify the cognitive therapy system of Vaughan as modified to include a gratitude journal, as taught by Hernandez, because it is a holistic approach that addresses wellness on every level (Hernandez ¶[0022]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Patent Application Publication No. 2021/0100491 to Bojan teaches a plurality of treatment modalities and assessment of responses.
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/AMANDA L STEINBERG/Examiner, Art Unit 3792