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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/14/2025 has been entered. Claims 1-20 are pending.
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 1 – 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1: Is the claimed invention a statutory category of invention?
Claims 1, 10 and 16 are directed to a mobile device, a method and a computer program for generating a modified therapy plan (Step 1, Yes).
Step 2A, Prong 1: Does the claim recite an abstract idea?
The limitation of steps: … receiving motion sensor data generated by a motion sensor of a wearable device worn by a user, the motion sensor data generated by the motion sensor in response to a predetermined gesture-based movement of the wearable device while the user is performing a postoperative therapy plan exercise, the predetermined gesture-based movement including a user-initiated command gesture that is distinct from the postoperative therapy plan exercise: initiating a session in response to the predetermined gesture-based movement; automatically identifying, during the session, a number of repetitions of a predetermined repetitive motion gesture by the wearable device based on the motion sensor data; and generating, in response to identifying the number of repetitions of the predetermined repetitive motion gesture at an end of the session, a modified therapy plan exercise based on the postoperative therapy plan exercise and the predetermined repetitive motion gesture as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind of a fitness trainer but for the recitation of generic computer components (claim 1 and 16) and the data acquisition element (motion sensor). The claimed method akin to mental process of observations the motion, evaluations motion gesture, and generating a modified therapy plan. The mere nominal recitation of processing circuitry of a mobile device performing these steps does not take the claim limitation outside of the mental processes grouping. Thus, the claim recites a mental process (Step 2A, Prong 1: yes).
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application?
Per the 2019 Revised Patent Subject Matter Eligibility Guidance, if a claim as a whole integrates the recited judicial exception into a practical application of that exception, a claim is not "directed to" a judicial exception. Alternatively, a claim that does not integrate a recited judicial exception into a practical application is directed to the exception. Evaluating whether a claim integrates an abstract idea into a practical application is performed by a) identifying whether there are any additional elements recited in the claim beyond the abstract idea, and b) evaluating those additional elements individual and in combination to determine whether they integrate the abstract idea into a practical application, using one or more of the considerations laid out by the Supreme Court and the Federal Circuit. Exemplary considerations indicative that an additional element (or combination of elements) may have or has not been integrated into a practical application are set forth in the 2019 PEG
With respect to the instant claims, Claims 1, 10, 16 recite the additional elements of: a wearable device, a motion sensor, a mobile device, a processing circuitry. It is particularly noted that the use of mobile device and processing circuitry "as a tool" to perform an abstract method and steps for receiving motion sensor device that only amount to extra solution activity are indicated in the 2019 PEG as examples that an additional element has not been integrated into a practical application. Even in combination, the recited additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits, such as an improvement to a computing system, on practicing the abstract idea (STEP 2A, Prong 2: NO).
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Claims 1, 10, 16 recite the additional elements of: a wearable device, a motion sensor, a mobile device, a processing circuitry set forth above for Step 2A, Prong 2. Regarding these limitations: Applicant's specification describes these features in generic manner "… A wearable device may include a watch, a device with a sensor, or another device that may be attached to the body of the patient in some manner (e.g., embedded in clothing or a shoe). A mobile device includes a phone, such as an iPhone or an Android-based device, or a tablet” in the Applicant’s published application, para. [0014]). There is no indication in the Specification that Applicants have achieved an advancement or improvement in computing device that generates therapy plan and motion sensing technology. Dependent claims 2 – 9, 11 – 15, 17 – 20 inherit the deficiencies of their respective parent claims through their dependencies and do not recite additional limitations sufficient to direct the claims to more than the claimed abstract idea, and are thus rejected for the same reasons.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2,5,10-11,16-17 and 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Avni et al. (US 2013/0236867 A1).
Re claims 1, 10, 16:
Avni teaches 1. A mobile device communicatively coupled to a wearable device (Avni, [0151]; [0153]; fig. 7; [0149]), the mobile device comprising:
processing circuitry (Avni, [0335]) configured to:
receiving motion sensor data generated by a motion sensor of a wearable device worn by a user (Avni, [0149]; [0153], “strapped to the patient’s ankle”; [0319]), the motion sensor data generated by the motion sensor in response to a predetermined gesture-based movement of the wearable device while the user is performing a postoperative therapy plan exercise (Avni, [0037], “a gait analysis”; [0342], “The system detects the patient's gait pattern and deviations in different pathologies”; [0123], “appropriate therapy regimen for the patient to rehabilitate to a normal gait pattern”; [0122]; [0126]), the predetermined gesture-based movement including a user-initiated command gesture that is distinct from the postoperative therapy plan exercise (Avni, [0254], “Click Start Exercise to begin the session”; fig. 47, “Start Exercise”; [0259]; [0287[; [0331]);
initiate a session in response to the predetermined gesture-based movement (Avni, [0254], “Click Start Exercise to begin the session”; fig. 47, “Start Exercise”; [0259]; [0287[; [0331]);
automatically identifying, during the session, a number of repetitions of a predetermined repetitive motion gesture by the wearable device based on the motion sensor data (Avni, [0153], “The software loaded into the control unit or provided as part of the display software then guides the therapist through building a therapy regimen (program) for the patient by establishing weight bearing thresholds, exercises, repetition, timing, feedback modalities, etc.”; [0343]; [0359]; [0384], “repetitions in each exercise”); and
generating, in response to identifying the number of repetitions of the predetermined repetitive motion gesture at an end of the session, a modified therapy plan exercise based on the postoperative therapy plan exercise and the predetermined repetitive motion gesture (Avni, [0247], “Training program parameters can be modified … The software analyzes the results (patient compliance score) and updates the program according to difficulty level to adjust patient trend--improvement/plateau or not comply/deterioration”; [0359] – [0360], “The training program may also be updated … The updates are generally based on patient performance compliance and or/progress reports that are sent back to the clinics at the end of each exercise”; [0041]; [0231], “Repetitions--number of repetition during each of the training exercises Repetition success=Compliance score”).
10. A method (Avni, [0151]; [0153]; fig. 7; [0149]; [0335]) comprising:
receiving motion sensor data generated by a motion sensor of a wearable device worn by a user (Avni, [0149]; [0153], “strapped to the patient’s ankle”; [0319]), the motion sensor data generated by the motion sensor in response to a predetermined gesture-based movement of the wearable device while the user is performing a postoperative therapy plan exercise (Avni, [0037], “a gait analysis”; [0342], “The system detects the patient's gait pattern and deviations in different pathologies”; [0123], “appropriate therapy regimen for the patient to rehabilitate to a normal gait pattern”; [0122]; [0126]), the predetermined gesture-based movement including a user-initiated command gesture that is distinct from the postoperative therapy plan exercise (Avni, [0254], “Click Start Exercise to begin the session”; fig. 47, “Start Exercise”; [0259]; [0287[; [0331]);
initiate a session in response to the predetermined gesture-based movement (Avni, [0254], “Click Start Exercise to begin the session”; fig. 47, “Start Exercise”; [0259]; [0287[; [0331]);
automatically identifying, during the session, a number of repetitions of a predetermined repetitive motion gesture by the wearable device based on the motion sensor data (Avni, [0153], “The software loaded into the control unit or provided as part of the display software then guides the therapist through building a therapy regimen (program) for the patient by establishing weight bearing thresholds, exercises, repetition, timing, feedback modalities, etc.”; [0343]; [0359]; [0384], “repetitions in each exercise”); and
generating, in response to identifying the number of repetitions of the predetermined repetitive motion gesture at an end of the session, a modified therapy plan exercise based on the postoperative therapy plan exercise and the predetermined repetitive motion gesture (Avni, [0247], “Training program parameters can be modified … The software analyzes the results (patient compliance score) and updates the program according to difficulty level to adjust patient trend--improvement/plateau or not comply/deterioration”; [0359] – [0360], “The training program may also be updated … The updates are generally based on patient performance compliance and or/progress reports that are sent back to the clinics at the end of each exercise”; [0041]; [0231], “Repetitions--number of repetition during each of the training exercises Repetition success=Compliance score”).
16. A non-transitory machine-readable medium comprising instructions that, when executed by processing circuitry of a mobile device, the instructions causing the mobile device to perform operations (Avni, [0151]; [0153]; fig. 7; [0149]; [0335]) comprising:
receive motion sensor data generated by a motion sensor of a wearable device worn by a user (Avni, [0149]; [0153], “strapped to the patient’s ankle”; [0319]), the motion sensor data generated by the motion sensor in response to a predetermined gesture-based movement of the wearable device while the user is performing a postoperative therapy plan exercise (Avni, [0037], “a gait analysis”; [0342], “The system detects the patient's gait pattern and deviations in different pathologies”; [0123], “appropriate therapy regimen for the patient to rehabilitate to a normal gait pattern”; [0122]; [0126]), the predetermined gesture-based movement including a user-initiated command gesture that is distinct from the postoperative therapy plan exercise (Avni, [0254], “Click Start Exercise to begin the session”; fig. 47, “Start Exercise”; [0259]; [0287[; [0331]);
initiate a session in response to the predetermined gesture-based movement (Avni, [0254], “Click Start Exercise to begin the session”; fig. 47, “Start Exercise”; [0259]; [0287[; [0331]);
automatically identifying, during the session, a number of repetitions of a predetermined repetitive motion gesture by the wearable device based on the motion sensor data (Avni, [0153], “The software loaded into the control unit or provided as part of the display software then guides the therapist through building a therapy regimen (program) for the patient by establishing weight bearing thresholds, exercises, repetition, timing, feedback modalities, etc.”; [0343]; [0359]; [0384], “repetitions in each exercise”); and
generating, in response to identifying the number of repetitions of the predetermined repetitive motion gesture at an end of the session, a modified therapy plan exercise at the mobile device based on the postoperative therapy plan exercise and the predetermined repetitive motion gesture (Avni, [0247], “Training program parameters can be modified … The software analyzes the results (patient compliance score) and updates the program according to difficulty level to adjust patient trend--improvement/plateau or not comply/deterioration”; [0359] – [0360], “The training program may also be updated … The updates are generally based on patient performance compliance and or/progress reports that are sent back to the clinics at the end of each exercise”; [0041]; [0231], “Repetitions--number of repetition during each of the training exercises Repetition success=Compliance score”).
Re claims 2, 11, 17:
2. The mobile device of claim 1, wherein the processing circuitry is further configured to(Avni, [0149]; [0153], “strapped to the patient’s ankle”, “The software loaded into the control unit or provided as part of the display software then guides the therapist through building a therapy regimen (program) for the patient by establishing weight bearing thresholds, exercises, repetition, timing, feedback modalities, etc.”; [0319]; [0037], “a gait analysis”; [0342], “The system detects the patient's gait pattern and deviations in different pathologies”; [0123], “appropriate therapy regimen for the patient to rehabilitate to a normal gait pattern”; [0122]; [0126], “a therapy regimen (program) for the patient by establishing weight bearing thresholds, exercises, repetition, timing, feedback modalities, etc.”; [0343]; [0359]; [0384], “repetitions in each exercise”; [0040], “monitoring the patient's compliance with the provided objective therapy regimen”).
Re claim 5:
5. The mobile device of claim 1, wherein the processing circuitry is further configured to display the modified therapy plan exercise on the mobile device (Avni, [0041]).
Re claim 19:
19. The non-transitory machine-readable medium of claim 16, the operations further comprising: analyzing the motion sensor data to determine exercise form accuracy; and generating feedback based on detected form deviations (Avni, [0133], “Gait deviations”; [0323]; [0177], “above”, “upper”; [0359], “builds a training program including a clinical and home based protocol that includes a number of specific functional exercises with the specific thresholds, feedback location, time/repetition, time in the target”; [0378], “reach the lower target”; [0384]).
Claim Rejections - 35 USC § 103
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 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 3-4,6-7,12-14 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Avni et al. (US 2013/0236867 A1) in view of Flaherty (US 2016/0220867 A1).
Re claims 3, 12, 18:
3. The mobile device of claim 2, wherein the processing circuitry is further configured to: send the exercise adherence metric to a server; and receive an updated therapy from the server including a modification to a future adherence metric. 12. The method of claim 11, further comprising: sending the exercise adherence metric to a server; and receive an updated therapy from the server including a modification to a future adherence metric. 18. The non-transitory machine-readable medium of claim 17, the operations further comprising: sending the exercise adherence metric to a server; and receiving an updated therapy from the server including a modification to a future adherence metric (Avni, [0041], “guide the user through the therapy regimen and that enable a therapist to vary force thresholds in the therapy as appropriate to modify the therapy regimen”; [0148], “monitor the patient's compliance with the prescribed therapy regimen, and adjust the therapy regimen based on the patient's performance”; [0361], “the application will automatically update the training program and increase the difficulty level or reduce the difficulty level when the patient does not successfully complete the training program”).
Avni doe not explicitly disclose modify receive an updated therapy calendar entry; instead Avni teaches receiving an updated therapy regimen and a weekly calendar (Avni, [0382]; [0360]).
Flaherty teaches Systems, methods, devices, and computer programs for generating personalized fitness programs (Flaherty, Abstract). Flaherty further teaches the operations further comprising: sending the exercise adherence metric to a server; and receive an updated therapy calendar entry from the server including a modification to a future adherence metric (Flaherty, [0028], “the method may automatically adjust the initial schedule to generate a revised schedule, based on the detected physical activity. In some embodiments, the adjustment of the initial schedule may involve reorganizing the existing exercises and activities into a new order or schedule”; [0029]; [0039], “the fitness program system 105 may receive a revised target performance metric and may be configured to update the expected completion date or update the user's fitness program based on the new desired target performance metric from the user 102b”). Therefore, in view of Flaherty, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the mobile device / method described in Avni, by updating therapy calendar entry as taught by Flaherty, since the generated exercise schedule may be merged or synchronized with the user's general calendar (or non-exercise program calendar) and may be configured to provide the user with prompts or reminders regarding scheduled exercises and/or activities (Flaherty, [0029]).
Re claims 4, 13:
4. The mobile device of claim 2, wherein the processing circuitry is further configured to automatically modify a therapy calendar based on the tracking information. 13. The method of claim 12, further comprising automatically modifying the updated therapy calendar entry based on the tracking information (Avni, [0041], “guide the user through the therapy regimen and that enable a therapist to vary force thresholds in the therapy as appropriate to modify the therapy regimen”; [0148], “monitor the patient's compliance with the prescribed therapy regimen, and adjust the therapy regimen based on the patient's performance”; [0361], “the application will automatically update the training program and increase the difficulty level or reduce the difficulty level when the patient does not successfully complete the training program”; Flaherty, [0028], “the method may automatically adjust the initial schedule to generate a revised schedule, based on the detected physical activity. In some embodiments, the adjustment of the initial schedule may involve reorganizing the existing exercises and activities into a new order or schedule”; [0029]; [0039], “the fitness program system 105 may receive a revised target performance metric and may be configured to update the expected completion date or update the user's fitness program based on the new desired target performance metric from the user 102b”).
Re claim 14:
14. The method of claim 10, further comprising presenting, on a user interface on a display device, a therapy calendar, the therapy calendar displaying at least a portion of a plurality of postoperative therapy plan calendar entries (Flaherty, figs. 10 – 12; [0028] – [0029]; [0039]).
Re claim 6:
6. The mobile device of claim 1, comprising a display device configured to present, on a user interface, a therapy calendar displaying at least a portion of a plurality of postoperative therapy plan calendar entries (Flaherty, figs. 10 – 12; [0028] – [0029]; [0039]).
Re claim 7:
7. The mobile device of claim 6, wherein the processing circuitry is further configured to: analyze the motion sensor data to determine exercise form accuracy; and generate feedback based on detected form deviations (Avni, [0133], “Gait deviations”; [0323]; [0177], “above”, “upper”; [0359], “builds a training program including a clinical and home based protocol that includes a number of specific functional exercises with the specific thresholds, feedback location, time/repetition, time in the target”; [0378], “reach the lower target”; [0384]).
Claims 9 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Avni et al. (US 2013/0236867 A1) and Flaherty (US 2016/0220867 A1) as applied to claims 6 and 14 above, and further in view of Urbanowski et al. (US 2012/0251990 A1).
Re claims 9, 15:
Avni does not explicitly disclose a questionnaire, nor disclose a video of the exercise.
Urbanowski et al. (US 20120251990 A1) teaches an interactive, dynamic system for athletic training (Urbanowski, Abstract). Urbanowski further teaches 9. The mobile device of claim 6, wherein: the display device is further configured to present, on the user interface, at least one question of a questionnaire; and the processing circuitry is further to send a video of the postoperative therapy plan exercise to the display device in response to receiving an answer to the at least one question. 15. The method of claim 14, further comprising: presenting, on the user interface, at least one question of a questionnaire; and sending a video of the postoperative therapy plan exercise to a user device for display in response to receiving an answer to the at least one question (Urbanowski, Abstract, “A system for creating a personalized, dynamic, multi-sport training plan for a user comprises a question generating module; a user input module which accepts user answers to questions generated by the question generating module and accepts other inputs relating to the user; and a processing module which collects and analyzes the answers to the questions and the inputs and thereafter, based at least in part on a calculation of an exponential moving average ("EMA") of said answers, creates a training schedule for each sport, which is dynamically linked to all previous user inputs; wherein the question generating module, by way of an intelligent link to all previous user inputs and feedback direction from the processing module, creates a plurality of further questions for the user to enable modifications to be made to training schedule”; [0083], “The calendar consists of specific workout routines for each sport, for each day. Each set of workout routines consists of specific workout instructions with related videos illustrating how the workouts are to be conducted”). Therefore, in view of Urbanowski, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the mobile device and computer program described in Avni, by providing questionnaire and video instructions as taught by Urbanowski, since related videos illustrates how the workouts are to be conducted (Urbanowski, [0083]) and the questionnaires can create a personalized, dynamic, multi-sport training plan for a user (Urbanowski, [0049] – [0052]).
Claims 8 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Avni et al. (US 2013/0236867 A1) in view of Gamlyn et al. (US 5,749,367).
Re claims 8, 20:
8. The mobile device of claim 1, wherein the processing circuitry is further configured to: monitor background activity metrics based on information recorded by a sensor of the wearable device, the background activity metrics including at least one of stairs climbed, steps taken, or heart rate. 20. The non-transitory machine-readable medium of claim 16,the operations further comprising: monitoring background activity metrics including at least one of stairs climbed, steps taken, or heart rate (Avni, fig. 51; [0264]; Flaherty, [0036]; [0134], “builds a training program including a clinical and home based protocol that includes a number of specific functional exercises with the specific thresholds, feedback location, time/repetition, time in the target”).
Avni does not explicitly disclose generating alerts when activity patterns indicate potential patient distress.
Gamlyn et al. (US 5,749,367) teaches a heart monitoring apparatus and method wherein an electrocardiograph signal is obtained from a patient and processed to enhance the salient features and to suppress noise. Gamlyn teaches monitoring background activity metrics including at least one of stairs climbed, steps taken, or heart rate; and generating alerts when activity patterns indicate potential patient distress (Gamlyn, col. 16, lines 15 – 37, “the visual or audible output can indicate the level of stress experienced by the heart, or could more specifically provide a warning when specific heart conditions are detected or an undesirable change in the operation of the heart is detected for a patient”). Therefore, in view of Gamlyn, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the mobile device and computer program described in Avni, by providing the alerts as taught by Gamlyn, since the alarm can indicate a deterioration in the condition of the patient (Gamlyn, col. 4, lines 1- 15).
Response to Arguments
Applicant's arguments filed 11/14/2025 have been fully considered but they are not persuasive.
Applicant argues that about what the claims "cover" is an allegation that the claims, at best, merely involve an exception. Because the claims do not recite an exception, the claims are eligible and do not require further eligibility analysis.
The Office submits that claims 1, 10, 16 directed to a judicial exception (i.e., an abstract idea) without significantly more. The processing circuitry and motion sensor are recited so generically (no details whatsoever are provided other than that they are a processor and a data acquisition device) that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(1) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank lnt'l, 573 U.S. 208, 224-26 (2014).
Applicant argues that the amended claims integrate any alleged judicial exception into a practical application through at least three distinct technical elements that impose meaningful limitations … coordinated processing of gesture-based session initiation provides improved accuracy and control in postoperative therapy monitoring systems. This goes beyond generic data processing by incorporating specialized motion sensor interpretation that distinguishes between deliberate command gestures and therapeutic exercise movements, using real-time pattern recognition algorithms that cannot be performed practically in the human mind … amended claim 1. This recited feature cannot practically be performed in the human mind, particularly the real-time motion sensor data analysis, session-based repetition counting, and automated therapy plan modification at the scale and precision required for postoperative rehabilitation. As emphasized in the August 4, 2025 USPTO memo, "a claim does not recite a mental process when it contains limitation(s) that cannot practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitation(s)."
The examiner submits that “processing of gesture-based session” could be as simple as counting steps, measuring distance runs, and a number of pushups performed by the user. People has been known to create and modify training routine based on the exercise metrics. Although keeping track of motion data could require large amounts of data, and the use of computers indeed may speed up these processes, these data analysis steps can be performed in the human mind with pen and paper. See Ans. 3 (noting that a person is capable of dividing data into equal segments, averaging, dividing, and comparing to a threshold). Indeed, humans routinely processed large amounts of data by hand before the advent of computers. As court has explained, "the fact that the required calculations could be performed more efficiently via a computer does not materially alter the patent eligibility of the claimed subject matter." Bancorp Servs., L.L.C. v. Sun Life Assur. Co. of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012).
Applicant argues that Applicant submits that the presently amended independent claims 1, 10, and 16 recite specific technological solutions that improve computer functionality. Under MPEP § 2106, a claim reciting a judicial exception is not directed to the judicial exception if it also recites additional elements demonstrating that the claim as a whole integrates the exception into a practical application, specifically when "the claimed invention improves the functioning of a computer or improves another technology or technical field."
The examiner submits that claims 1, 10 and 16 recite “A mobile device communicatively coupled to a wearable device, the mobile device comprising: processing circuitry configured to: receive motion sensor data generated by a motion sensor of a wearable device”. The limitations of a motion sensor configured to acquire count repetitions of an exercise (i.e., counting steps, push ups or squats) consist of steps of mere data acquisition which is extra solution activity that does not provide a practical application of an abstract method. In light of the high level of generality with which Applicant's specification describes the motion sensor as “A wearable device may be strapped or otherwise coupled to an ankle or knee to detect reps or time of an exercise using the knee. Other sensors or wearable devices may be attached to different body parts ( or moved around) corresponding to a routine or exercise performed. For example, a local body network may be used, with sensors, such as an inertial measurement unit (IMU) or nine-axis sensor ( e.g., including an accelerometer, a gyroscope, and a magnetometer), or other location, movement, or acceleration detecting sensor, placed on different body parts ( e.g., knee, thigh, ankle, hip, etc.).”. Examiner concludes that Applicant's specification describes the recited the motion sensor in a manner that indicates that the elements are sufficiently well-known that the specification does not need to describe the particulars of these additional elements to satisfy the 35 U.S.C. 112(a) written description requirement.
Applicant argues that [A]mended independent claims 1, 10, and 16 are analogous to the claims in Desjardins because they recite specific technical implementations involving motion sensor gesture recognition, session-based therapy monitoring, automated repetition analysis, and real-time therapy plan modification that improve computer functionality for postoperative care management. Features that provide an improvement in computer functionality are recited in the claims, such as the coordinated operation of gesture detection and therapy session management, real-time motion analysis during discrete therapy sessions, and automated modification of therapy plans based on performance metrics, as recited in amended independent claim 1.
The examiner submits that the newly amended limitation: “the predetermined gesture-base movement including a user-initiated command gesture that is distinct from the postoperative therapy plan exercise; initiate a session in response to the predetermined gesture-based movement”. Based on the broadest reasonable interpretation, the “user-initiated command gesture” could be as simple as a start button as shown in applicant’s own figure 1 shown below. There is nothing technological about a start button (“user-initiated command gesture”), nor it requires any sophisticate pattern detection, nor requires real time processing of the so call real-time motion analysis.
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Applicant’s published application, fig. 1
Applicant analogizes the independent claims to the claims in Desjardins that integrated an abstract idea (a mathematical calculation) into a practical application. In Desjardins, the Appeals Review Panel determined that the specification identified “improvements in training the machine learning model itself,” i.e., reduced storage requirements and reduced system complexity. The ARP also determined that “the claims reflect such an improvement.” Here, in contrast to Desjardins, the current specification does not identify “improvements in training the machine learning model itself.” Also, the claims invoke processing circuitry and motion sensors merely as a tool and apply techniques to identify some exercise metrics (number of repetitions).
Applicant argues that Fourth, Applicant submits that the claimed features amount to significantly more than any allegedly abstract idea because of the non-conventional and non-generic arrangement of technical features that provide specific improvements to computer functionality.
The examiner submits that claims 1, 10 and 16 recite “A mobile device communicatively coupled to a wearable device, the mobile device comprising: processing circuitry configured to: receive motion sensor data generated by a motion sensor of a wearable device”. The limitations of a motion sensor configured to acquire count repetitions of an exercise (i.e., counting steps, push ups or squats) consist of steps of mere data acquisition which is extra solution activity that does not provide a practical application of an abstract method. In light of the high level of generality with which Applicant's specification describes the motion sensor as “A wearable device may be strapped or otherwise coupled to an ankle or knee to detect reps or time of an exercise using the knee. Other sensors or wearable devices may be attached to different body parts ( or moved around) corresponding to a routine or exercise performed. For example, a local body network may be used, with sensors, such as an inertial measurement unit (IMU) or nine-axis sensor ( e.g., including an accelerometer, a gyroscope, and a magnetometer), or other location, movement, or acceleration detecting sensor, placed on different body parts ( e.g., knee, thigh, ankle, hip, etc.).”. Examiner concludes that Applicant's specification describes the recited the motion sensor in a manner that indicates that the elements are sufficiently well-known that the specification does not need to describe the particulars of these additional elements to satisfy the 35 U.S.C. 112(a) written description requirement.
Applicant argues that Fourth, Applicant's amended claims satisfy the improvements consideration under MPEP § 2106.0S(a) by reciting specific improvements to computer processing capabilities for postoperative therapy management. The claims address the technical problems described in the specification of patient adherence failures in postoperative therapy due to inconvenient in-office requirements, missed sessions, where"[c]are teams also have poor visibility into patient adherence to prescribed prehab or therapy and are unable to track what educational items patients have completed or how the patients are feeling post surgery." The technical solutions described in the specification include "[s]ystems and methods [that] may use a mobile device communicatively coupled to a wearable device to present an exercise to a user" with "automatic tracking of adherence to the routine" through "sensors on the wearable device [that] may be used for gesture-based controls (e.g. shake fist to redo routine, double tap hip to add extra repetitions)"
The examiner submits that “sensors on the wearable device [that] may be used for gesture-based controls (e.g. shake fist to redo routine, double tap hip to add extra repetitions)" are not recited in the claims. Second, based on the broadest reasonable interpretation, the “user-initiated command gesture” could be as simple as a start button as shown in applicant’s own figure 1.
In rejecting claim 1, the Office Action acknowledges that "Avni does not explicitly disclose the predetermined gesture-based movement initiating a session," and cites to Venkatraman as allegedly disclosing the same.23 However, Venkatraman teaches away from user-initiated command gestures. Venkatraman's objective is to eliminate user input entirely, as evidenced by its repeated emphasis on automatic exercise detection without user input. For example, Venkatraman states "the techniques described herein may allow a user to start and/or end an exercise without manual input or interaction with the wearable device 100, and the wearable device 100 may be able to automatically start and/or stop the tracking of the exercise,"24 and "[c]ertain aspect of this disclosure relate to the automated detection and logging of data relating to the start and/or end of the exercise without any manual intervention."25 Applicant's claimed "predetermined gesture-based movement including a user-initiated command gesture that is distinct from the postoperative therapy plan exercise" represents a deliberate and predetermined user action that provides a command signal to transition the system into session monitoring mode. Furthermore, neither reference teaches Applicant's claimed temporal and functional separation between the command gesture (which initiates the session) and the therapeutic exercise movements (which are counted during the session). This architectural distinction is absent from both Avni's continuous monitoring and Venkatraman's automatic detection approach. Venkatraman's automatic and passive detection of exercise movements "without any manual intervention,"26 alone or combined with Avni, does not teach or suggest "processing circuitry configured to: receive motion sensor data generated by a motion sensor of a wearable device ·worn by a user, the motion sensor data generated by the motion sensor in response to a predetermined gesture-based movement of the wearable device while the user is performing a postoperative therapy plan exercise, the predetermined gesture-based movement including a user-initiated command gesture that is distinct from the postoperative therapy plan exercise" and "initiate a session in response to the predetermined gesture-based movement" as recited in amended claim 1.
Applicant amended the claims 1, 10 and 16 to include a “user-initiated command gesture that is distinct from the postoperative therapy plan exercise”. The examiner submits that both Avni and Venkatraman (not cited for this office action) teach a distinct user command gesture that initiates an exercise session. For example, In. para. 259, Avni states “When the user has finished defining the exercise in the workout plan design screen, the user clicks start exercise to begin”; In. para. 254, “Click Start Exercise to begin the session”; and [0287[; [0331] and fig. 47, “Start Exercise” button. Avni teaches a user selectable command to start an exercise, wherein the command is distinct from the sensor data for recording the number of repetitions of the motion gesture. Venkatraman also teaches a distinct user-initiated command gesture to start an exercise session (Venkatraman, [0053], “The tracking of these exercises may involve the user manually indicating the start of an exercise by pressing a start button of a wearable device 100 or a connected client device 170”). The Office interpretation of “user-initiated command gesture” comply with applicant’s own disclosure in fig. 1 with a start button.
Conclusion
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/JACK YIP/Primary Examiner, Art Unit 3715
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