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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 March 18, 2026 has been entered.
Response to Amendment
In the amendment filed on March 18, 2026, the following has occurred: claim(s) 1, 9, 17 have been amended. Now, claim(s) 1-20 are pending.
Notice to Applicant
The Examiner has withdrawn the 35 U.S.C. 101 rejection(s) in light of the claims. The addition to independent claims 1, 9, and 17 of “based on the exercise plan, controlling, while the user performs the exercise plan on the electromechanical device, a physical portion of the electromechanical device via a control instruction specifying an operating parameter of the physical portion of the electromechanical device associated with the exercise plan, wherein the control instruction specifying the operating parameter is transmitted to the electromechanical device to adjust the operating parameter of the electromechanical device” combined with the presented steps and specifically the step of “transmitting the exercise plan to a computing device associated with the electromechanical device” recites a combination to improve an improvement to the technological field of controlling operation of electromechanical exercise devices and integrates the abstract idea into a practical application. The 35 U.S.C. 101 rejection(s) are withdrawn.
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rose et al. (U.S. Patent Pre-Grant Publication No. 2021/0050086) in view of Jang et al. (U.S. Patent Pre-Grant Publication No. 2017/0291067) in further view of Hacking et al. (U.S. Patent Pre-Grant Publication No. 2020/0289881).
As per independent claim 1, Rose discloses a computer-implemented method for generating, an exercise plan for a user to perform, wherein the method comprises, using one or more processing devices:
receiving data pertaining to the user, wherein the data comprises the user fitness test results (See Fig. 2 and Paragraphs [0084], [0168]-[0183]: User specific genetic and environmental data are collected from genetic and environmental collection sources, environmental data can be health and fitness applications, which the Examiner is interpreting the health and fitness applications as environmental data to encompass the user fitness test results);
generating, the exercise plan, wherein the generating is based at least on the user energy consumption metrics and a user energy score (See Fig. 4a-4c and Paragraphs [0049], [0083]-[0087], [0305]-[0308], [0474]: Different workout plans can be matched to users goals or needs, which the Examiner is interpreting workout plans to encompass exercise plans, and interpreting trait scores to encompass a user energy score, and interpreting energy expenditure to encompass the user energy consumption metrics when combined with Jang’s teachings of “generate and provide the personalized exercise program using personalized metabolic equivalent of task (MET) information and a target exercise amount”), wherein the exercise plan includes at least a subset of the plurality of exercises to be performed by the user to attempt to achieve the user energy score (See Paragraphs [0330]-[0333]: The selector algorithm interrogates the tagged data held within banks of matrices in the exercise datasets, these datasets include descriptions of exercises (e.g. type of movement/resistance/equipment/muscle groups) as well as exercise parameters, e.g. sets and rep choices and warm up routines, which the Examiner is interpreting the exercise datasets to encompass a subset of the plurality of exercises to be performed by the user to attempt to achieve the user energy score), wherein each of a plurality of levels of attainment comprising range of motion, strength, endurance, balance, and mobility are associated with at least some of the subset of the plurality of exercises (See Paragraphs [0310]-[0316], [0330]-[0333]: The trait profile can be considered to be the user's health status or ‘biological avatar’ and provides an indication of the user's likely biological, physiological and/or behavioural response to a fitness programme, and the system can then determine a fitness programme that is tailored to achieving the goals of the user, which the Examiner is interpreting achieving the goals of the user to encompass a plurality of levels of attainment comprising range of motion, strength, endurance, balance, and mobility are associated with at least some of the subset of the plurality of exercises as the recommendations are generally related to exercise (exercise type, frequency, etc.) as the exercise type relates to range of motion, strength, endurance, balance, and mobility), and each of the plurality of levels of attainment is assigned a respective priority percentage for a plurality of periods of time associated with the exercise plan (See Paragraphs [0145], [0221], [0464]: Once the trait scores for an individual have been calculated and utilised to understand the physiological makeup of the biological systems of the user, it may be possible to begin the recommendation process, trait scores can be fixed at any given point in time, the fitness, diet plans given to the user are then based on the hierarchical compound weighting of traits associated with particular goal-linked questions and their effects on the biological systems to produce a readout figure, which the Examiner is interpreting a fixed schedule for the priority exercises of the program to encompass a respective priority percentage, and interpreting the fitness given to the user are then based on the hierarchical compound weighting of traits associated with particular goal-linked questions and their effects on the biological systems to produce a readout figure to encompass a plurality of periods of time associated with the exercise plan), wherein the respective priority percentage shifts over the plurality of periods of time to ensure each of the plurality of levels of attainment is worked on during the exercise plan for the purpose of enabling the user to achieve the user energy score (See [0088], [0300], [0327]-[0329]: Conditions might include the location of training, equipment availability, type of cardio workout preference (e.g. running/cycling) and training day schedule to construct work out plans appropriate to the aspirations and preferences of the user, which the Examiner is interpreting type of cardio workout preference (e.g. running/cycling) and training day schedule to construct work out plans appropriate to the aspirations and preferences of the user to encompass the claimed portion as Rose utilizes an iterative process, fueled by the trait profile and user inputs, data associated with specific exercises is used to select appropriate and effective exercises and exercise programs from multiple exercise datasets, the identification of appropriate and effective exercises and exercise programs would be prioritized over inappropriate or ineffective exercises, and the diet and fitness recommendations may change any time a user updates or provides feedback to the system ([0300])), and wherein the user energy score corresponds to an amount of energy for the user to exert while performing the exercise plan (See Fig. 4a-4c and Paragraphs [0147], [0158]-[0168], [0422]-[0424]: The user data, and the trait scores are analysed to generate trait profiles which leverage understandings of the relationships, the interactions with the compound effects between the genetic and environmental data in order to generate a user profile, a trait profile can be generated for the user and the workout plan and/or recommendations provided by the system, the trait scores and biological system characterization are analysed within the trait and biological system model using customised algorithms or AI systems which leverage understandings of the relationships, interactions and compound effects between the traits and biological systems specific to the goal, which the Examiner is interpreting the workout plan to encompass the exercise plan, trait score and exercise parameters to encompass the user energy consumption metrics and a goal to encompass a user energy score, and the matching of relevant trait scores within the biological systems to appropriate schedules, exercises and exercise parameters to encompass the exercise plan includes at least a subset of the plurality of exercises to be performed by the user to attempt to achieve the user energy score, and interpreting the user's trait recommendations for recovery and lactate clearance are used to identify the exercise parameters for the identified exercises, i.e. the rest between exercises/sets, tempo to be used with the movement, and the effort level or rate of perceived exertion (RPE) required when performing the exercise or movement to encompass the user energy score corresponds to an amount of energy for the user to exert while performing the exercise plan ([0422]-[0424])); and
transmitting the exercise plan to a computing device associated with the electromechanical device (See Paragraph [0032]: The optimised workout plan may be transmitted to one or more of: a mobile phone app, desktop app, tablet app, email address, web browser, wearable electronic device, and an exercise machine, which the Examiner is interpreting the optimised workout plan to encompass the exercise plan and a mobile phone app, desktop app, tablet app, email address, web browser, wearable electronic device, and an exercise machine to encompass a computing device associated with the electromechanical device.)
While Rose teaches the method as described above, Rose may not explicitly teach generating, based on the user fitness test results, user energy consumption metrics for a plurality of exercises, wherein each of the user energy consumption metrics is generated for a respective one of the plurality of exercises based at least on a metabolic equivalent of task (MET) value for the respective one of the plurality of exercises and the user fitness test results.
Jang teaches a method for generating, based on the user fitness test results, user energy consumption metrics for a plurality of exercises, wherein each of the user energy consumption metrics is generated for a respective one of the plurality of exercises based at least on a metabolic equivalent of task (MET) value for the respective one of the plurality of exercises and the user fitness test results (See Fig. 1A and Paragraphs [0040]-[0050]: Embodiments may be applied to generate and provide the personalized exercise program using personalized metabolic equivalent of task (MET) information and a target exercise amount by generating the personalized MET information based on user information received or input through a device, the processor generates a personalized exercise program based on the target exercise amount and the personalized MET information, which the Examiner is interpreting generate and provide the personalized exercise program using personalized metabolic equivalent of task (MET) information and a target exercise amount to encompass generating, user energy consumption metrics for a plurality of exercises, wherein each of the user energy consumption metrics is generated for a respective one of the plurality of exercises based at least on a metabolic equivalent of task (MET) value for the respective one of the plurality of exercises and the user fitness test results.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the method of Rose to include generating, based on the user fitness test results, user energy consumption metrics for a plurality of exercises, wherein each of the user energy consumption metrics is generated for a respective one of the plurality of exercises based at least on a metabolic equivalent of task (MET) value for the respective one of the plurality of exercises and the user fitness test results as taught by Jang to be added to Rose's disclosure of customised algorithms that are utilized to analyze trait profiles that are used to identify an optimised workout plan for a user. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Rose with Jang with the motivation of generating a personalized exercise program (See Summary of Jang in Paragraph [0005]).
While Rose/Jang teaches the method as described above, Rose/Jang may not explicitly teach generating fitness test results while the user operates an electromechanical device;
based on the exercise plan, controlling, while the user performs the exercise plan on the electromechanical device, a physical portion of the electromechanical device via a control instruction specifying an operating parameter of the physical portion of the electromechanical device associated with the exercise plan, wherein the control instruction specifying the operating parameter is transmitted to the electromechanical device to adjust the operating parameter of the electromechanical device.
Hacking teaches a method for generating fitness test results while the user operates an electromechanical device (See Paragraphs [0018]-[0019]: The therapy device may include one or more sensors for measuring metric data associated with a patient's physical activities, and the metric data may be compared to acquired metric data and/or a set of a target values and feedback may be provided based on the comparison, which the Examiner is interpreting measuring metric data associated with a patient's physical activities to encompass fitness test results, and the therapy device to encompass an electromechanical device);
based on the exercise plan, controlling, while the user performs the exercise plan on the electromechanical device, a physical portion of the electromechanical device via a control instruction specifying an operating parameter of the physical portion of the electromechanical device associated with the exercise plan (See Fig. 3 and Paragraphs [0045]-[0048], [0052]-[0057], [0067]-[0070]: The control system may use information received from the monitoring devices to adjust parameters of components of the electromechanical device in real-time during a pedaling session, and enable a computing device operated by a physician to monitor the progress of a user participating in a treatment plan in real-time and/or to control operation of the electromechanical device during a pedaling session, the computing device may also use the steps taken and/or the heart rate to control a parameter of operating the electromechanical device, which the Examiner is interpreting control a parameter of operating the electromechanical device, and the movement of pedals ([0045]) to encompass a control instruction specifying an operating parameter of the physical portion of the electromechanical device associated with the exercise plan, and interpreting the control system to encompass an artificial intelligence engine as the control system can adjust parameters (e.g., reduce resistance provided by electric motor, increase resistance provided by the electric motor, increase/decrease speed of the electric motor, adjust position of pedals on radially-adjustable couplings, etc.) while operating the electromechanical device in the various modes), wherein the control instruction specifying the operating parameter is transmitted to the electromechanical device to adjust the operating parameter of the electromechanical device (See Fig. 4 and Paragraphs [0047]-[0058], [0064]-[0065], [0067]-[0076]: The control system may enable operating the electromechanical device in a variety of modes, such as a passive mode, an active-assisted mode, a resistive mode, and/or an active mode, the control system may use the information received from the measuring devices to adjust parameters (e.g., reduce resistance provided by electric motor, increase resistance provided by the electric motor, increase/decrease speed of the electric motor, adjust position of pedals on radially-adjustable couplings, etc.) while operating the electromechanical device in the various modes, which the Examiner is interpreting the control system may enable operating the electromechanical device and operating the electromechanical device in the various modes to encompass the control instruction specifying the operating parameter is transmitted to the electromechanical device to adjust the operating parameter of the electromechanical device.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the method of Rose/Jang to include generating fitness test results while the user operates an electromechanical device; based on the exercise plan, controlling, while the user performs the exercise plan on the electromechanical device, a physical portion of the electromechanical device via a control instruction specifying an operating parameter of the physical portion of the electromechanical device associated with the exercise plan, wherein the control instruction specifying the operating parameter is transmitted to the electromechanical device to adjust the operating parameter of the electromechanical device as taught by Hacking to generate data to be used by the method of Rose/Jang. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Rose/Jang with Hacking with the motivation of enhancing patient rehabilitation (See Detailed Description of Hacking in Paragraph [0044]).
Claim(s) 9 and 17 mirror claim 1 only within different statutory categories, and are rejected for the same reason as claim 1. The addition of "a memory device for storing instructions; and a processing device communicatively coupled to the memory device, the processing device configured to execute the instructions to" in claim 9 and "a tangible, non- transitory computer-readable medium storing instructions that, when executed, cause a processing device to" in claim 17 are disclosed by Rose in Paragraphs [0508]-[0509] that discloses that the methods can be implemented as a computer program and the computer may include a read only memory (ROM) and a physical computer readable medium, such as a disc or a memory device may provide the computer program.
As per claim 2, Rose/Jang/Hacking discloses the method of claim 1 as described above. Rose further teaches wherein the data pertaining to the user further comprises one or more user- reported pain levels, and wherein the user energy consumption metrics are further generated based on the one or more user-reported pain levels (See Paragraphs [0443]-[0445], [0452]-[0453], [0468]-[0469]: A new optimised workout plan can be generated based on the updated trait profile, feedback can be utilized by the system, the feedback may be emotional data input and exercise progression and regression, which the Examiner is interpreting the feedback may be emotional data input and exercise progression and regression to encompass pain levels as a user can identify if they are experiencing pain.)
Claim(s) 10 and 18 mirror claim 2 only within different statutory categories, and are rejected for the same reason as claim 2.
As per claim 3, Rose/Jang/Hacking discloses the method of claims 1-2 as described above. Rose further teaches wherein the user energy consumption metrics are further generated based on at least one selected from a group consisting of heart rate, step count, blood pressure, perspiration, blood oxygen levels, and body temperature (See Paragraphs [0128]-[0150], [0439]-[0469]: The feedback data itself may comprise data describing a physiological condition of the individual before, during, and/or after performing an exercise, for example a user's heart rate after an exercise has been completed, and environmental data can be digital information regarding the health, lifestyle and wellbeing of the individual which may include, but is not limited to, height, weight, age, blood pressure, body fat percentage, and fitness activity.)
Claim(s) 11 and 19 mirror claim 3 only within different statutory categories, and are rejected for the same reason as claim 3.
As per claim 4, Rose/Jang/Hacking discloses the method of claim 1 as described above. Rose further teaches wherein the user fitness test results indicate at least one selected from a group consisting of strength, mobility, endurance, pliability, a range of motion, flexibility, and balance (See Paragraphs [0112]: The system uses the genetic and environmental data to define a number of "traits", or propensities towards particular phenotypic expressions, and then uses these traits to model a smaller number of higher-level biological systems, a trait may be a physiological, behavioral or biological metric based on genetic and/or environmental factors, for example, endurance capability, workout recovery, etc.)
Claim(s) 12 and 20 mirror claim 4 only within different statutory categories, and are rejected for the same reason as claim 4.
As per claim 5, Rose/Jang/Hacking discloses the method of claim 1 as described above. Rose further teaches further comprising: receiving a physical activity goal the user desires to achieve, wherein the physical activity goal requires one or more physical levels of attainment to achieve (See Paragraphs [0128]-[0150]: Goal-specific Trait and Biological System Model, an algorithm used to modify scores based on weightings of traits associated with particular goal-linked questions and their effects on the biological systems to produce a readout, which the Examiner is interpreting the goal-linked questions when answered to encompass receiving a physical activity goal the user desires to achieve, wherein the physical activity goal requires one or more physical levels of attainment to achieve); and
determining the user energy score, wherein the user energy score is correlated with an amount of energy it takes to achieve the physical activity goal (See Paragraphs [0245]-[0250], [0474]: The question database provides a non-user specific overview of which traits are relevant to which category for a specific goal-related question and the categories can be assessed can be the "daily caloric intake" and "amount of carbohydrate" categories, which the Examiner is interpreting "daily caloric intake" to encompass an amount of energy as further discussed in Paragraph [0474].)
Claim(s) 13 mirrors claim 5 only within a different statutory category, and is rejected for the same reason as claim 5.
As per claim 6, Rose/Jang/Hacking discloses the method of claim 1 as described above. Rose further teaches further comprising: receiving updated user fitness test results (See Paragraphs [0485]-[0499]: Harvested data from a collection of users' data, or external/open source data, can be used to update the trait weightings that are used to generate trait profiles for all users, which the Examiner is interpreting updated trait weightings to encompass updated user fitness test results);
generating updated user energy consumption metrics for the plurality of exercises, wherein the generating is based at least on the updated user fitness test results (See Paragraphs [0485]-[0499]: Harvested data from a collection of users' data, or external/open source data, can be used to update the trait weightings that are used to generate trait profiles for all users, which the Examiner is interpreting updated trait weightings to encompass updated user fitness test results);
generating an updated exercise plan, wherein the generating is based at least on the updated user energy consumption metrics (See Paragraphs [0168], [0485]-[0499]: The user progresses through their health regime and experiences changes in their overall fitness and health, their diet, fitness and plans may then be updated by re-running the traits and biological system model in a sandbox environment, harvested data from a collection of users' data, or external/open source data, can be used to update the trait weightings that are used to generate trait profiles for all users, which the Examiner is interpreting updated trait weightings to encompass updated user fitness test results); and
transmitting the updated exercise plan to the computing device (See Paragraphs [0327]-[0438]: The optimised workout plan can be transmitted to an individual or healthcare practitioner.)
Claim(s) 14 mirrors claim 6 only within a different statutory category, and is rejected for the same reason as claim 6.
As per claim 7, Rose/Jang/Hacking discloses the method of claim 1 as described above. Rose further teaches further comprising generating one or more machine learning models trained to perform the generating of the user energy consumption metrics (See Paragraphs [0165]-[0168]: Trait scores and biological system characterization are analysed within the trait and biological system model using customised algorithms or AI system, which the Examiner is the trait and biological system model using customised algorithms or AI system to encompass generating one or more machine learning models.)
Claim(s) 15 mirrors claim 7 only within a different statutory category, and is rejected for the same reason as claim 7.
As per claim 8, Rose/Jang/Hacking discloses the method of claim 1 as described above. Rose further teaches further comprising: transmitting a signal to an exercise apparatus, wherein the user performs at least one of the subset of the plurality of exercises included in the exercise plan on the exercise apparatus (See Paragraphs [0333]-[0336]: As the user progresses through their workout plan, intra-workout feedback may be provided in many ways including telemetric through wearable devices, connect gym equipment, manual response to questionnaires or smart items, synced with the dynamic planner system, which the Examiner is interpreting the connected gym equipment or smart items to encompass the exercise apparatus as the workout plan may be uploaded directly to exercise machines in gyms); and
in response to the exercise apparatus receiving the signal, adjusting at least one portion of the exercise apparatus based on at least one operating parameter specified in the exercise plan (See Paragraphs [0331]-[0342]: As the user progresses through their workout plan, intra-workout feedback may be provided in many ways including telemetric through wearable devices, connect gym equipment, manual response to questionnaires or smart items, synced with the dynamic planner system, and the AI interpreter may ingest other personal data to guide plan adjustments and feedback data inputs can be utilized to adjust the plan, which the Examiner is interpreting adjusting the AI interpreter may ingest other personal data to guide plan adjustments and feedback data inputs can be utilized to adjust the plan to encompass adjusting at least one portion of the exercise apparatus based on at least one operating parameter specified in the exercise plan.)
As per claim 16, Rose/Jang/Hacking discloses the system of claim 9 as described above. Rose further teaches further including an exercise apparatus for the user to perform at least one of the subset of the plurality of exercises included in the exercise plan, wherein the processing device is further configured to execute the instructions to transmit a signal to the exercise apparatus (See Paragraphs [0333]-[0336]: As the user progresses through their workout plan, intra-workout feedback may be provided in many ways including telemetric through wearable devices, connect gym equipment, manual response to questionnaires or smart items, synced with the dynamic planner system, which the Examiner is interpreting the connected gym equipment or smart items to encompass the exercise apparatus as the workout plan may be uploaded directly to exercise machines in gyms), wherein, in response to the exercise apparatus receiving the signal, the exercise apparatus is configured to adjust at least one portion of the exercise apparatus based on at least an operating parameter specified in the exercise plan (See Paragraphs [0331]-[0342]: As the user progresses through their workout plan, intra-workout feedback may be provided in many ways including telemetric through wearable devices, connect gym equipment, manual response to questionnaires or smart items, synced with the dynamic planner system, and the AI interpreter may ingest other personal data to guide plan adjustments and feedback data inputs can be utilized to adjust the plan, which the Examiner is interpreting adjusting the AI interpreter may ingest other personal data to guide plan adjustments and feedback data inputs can be utilized to adjust the plan to encompass adjusting at least one portion of the exercise apparatus based on at least one operating parameter specified in the exercise plan.)
Response to Arguments
In the Remarks filed on March 18, 2026, the Applicant argues that the newly amended and/or added claims overcome the Claim Objection(s) and 35 U.S.C. 103 rejection(s). The Examiner acknowledges that the newly added and/or amended claims overcome the Claim Objection(s). However, the Examiner does not acknowledge that the newly added and/or amended claims overcome the 35 U.S.C. 103 rejection(s).
The Applicant argues that:
(1) Applicant respectfully asserts that the cited references, alone or in hypothetical combination, fail to teach or suggest every recitation of the amended independent claims. Applicant respectfully submits that the cited references fail to teach or suggest at least the portions of the amended independent claims. In the Office Action, the Office relies on Rose as allegedly teaching somewhat similar recitations previously included in the independent claims prior to the current amendments. Applicant respectfully asserts that above-reproduced portion of Rose merely discusses that trait scores for physiological, behavioural, and/or biological states of a user are used to query a database for exercises to include in an exercise plan. Rose does not teach or suggest levels of attainment comprising range of motion, strength, endurance, balance, and mobility being associated with a plurality of exercises, and each of the levels of attainment being assigned a respective priority percentage of a plurality of periods of time associated with the exercise plan. Applicant respectfully asserts that the traits of Rose are not equivalent to the levels of attainment as recited by the amended independent claims. Also, the trait scores of Rose are not equivalent to the priority percentages recited by the claims because Rose states that the ''trait score is intended to be indicative or define the likely biological, behavioural or physiological response of the user to the trait,'' and the priority percentages represent how important a respective level of attainment (e.g., range of motion) is to work on (e.g., perform associated exercises) during a given period of time (e.g., week 1 out of 5 weeks) for an exercise plan for a user to achieve a user energy score. (Rose, paragraph [0051].) In other words, a trait is an indication or definition of a characteristic of a user or of a specific biological, behavioural or physiological response of that user (e.g., user is male, user slows down or speeds up (behavior), user's blood pressure increases). None of these are in any way related to attainment of an objective defined in an exercise plan. One could attain or not attain an objective regardless of whether a user was male or female, regardless of whether a user slowed down or sped up, regardless of whether blood pressure became lower or higher. The objective stands by itself and therefore the attainment stands by itself and cannot be connected to the trait scores of Rose. In other words, objectives are independent variables, not dependent on any of the Rose traits. In addition to the foregoing, Rose does not teach or suggest that the trait scores are assigned to the traits for a plurality of periods of time associated with the exercise plan, as currently recited by the amended independent claims. Moreover, Rose is completely silent regarding the respective priority percentages shifting over the plurality of periods of time to ensure each of the levels of attainment are worked on during the exercise plan, as currently recited by the amended independent claims. The other cited references fail to cure these deficiencies of Rose. Accordingly, the cited references fail to teach or suggest all the recitations of the amended independent claims. Applicant respectfully requests that the Office withdraw this rejection of the claims and, further, allow the same.
In response to argument (1), the Examiner does not find the Applicant’s argument(s) persuasive. The Examiner maintains that the combination of Rose/Jang/Hacking teaches the newly amended independent claims 1, 9, and 17. The Examiner maintains that Rose teaches the newly amended claimed portion of “generating the exercise plan, wherein the generating is based at least on the user energy consumption metrics and a user energy score, wherein the exercise plan includes at least a subset of the plurality of exercises to be performed by the user to attempt to achieve the user energy score, wherein each of a plurality of levels of attainment comprising range of motion, strength, endurance, balance, and mobility are associated with at least some of the subset of the plurality of exercises, and each of the plurality of levels of attainment is assigned a respective priority percentage for a plurality of periods of time associated with the exercise plan, wherein the respective priority percentage shifts over the plurality of periods of time to ensure each of the plurality of levels of attainment is worked on during the exercise plan for the purpose of enabling the user to achieve the user energy score, and wherein the user energy score corresponds to an amount of energy for the user to exert while performing the exercise plan” as Rose describes in [0310]-[0316], [0330]-[0333]: The trait profile can be considered to be the user's health status or ‘biological avatar’ and provides an indication of the user's likely biological, physiological and/or behavioural response to a fitness programme, and the system can then determine a fitness programme that is tailored to achieving the goals of the user, which the Examiner is interpreting achieving the goals of the user to encompass a plurality of levels of attainment comprising range of motion, strength, endurance, balance, and mobility are associated with at least some of the subset of the plurality of exercises as the recommendations are generally related to exercise (exercise type, frequency, etc.) as the exercise type relates to range of motion, strength, endurance, balance, and mobility, Paragraphs [0145], [0221], [0464]: Once the trait scores for an individual have been calculated and utilised to understand the physiological makeup of the biological systems of the user, it may be possible to begin the recommendation process, trait scores can be fixed at any given point in time, the fitness, diet plans given to the user are then based on the hierarchical compound weighting of traits associated with particular goal-linked questions and their effects on the biological systems to produce a readout figure, which the Examiner is interpreting a fixed schedule for the priority exercises of the program to encompass a respective priority percentage, and interpreting the fitness given to the user are then based on the hierarchical compound weighting of traits associated with particular goal-linked questions and their effects on the biological systems to produce a readout figure to encompass a plurality of periods of time associated with the exercise plan, and in Paragraphs [0327]-[0329]: Conditions might include the location of training, equipment availability, type of cardio workout preference (e.g. running/cycling) and training day schedule to construct work out plans appropriate to the aspirations and preferences of the user, which the Examiner is interpreting type of cardio workout preference (e.g. running/cycling) and training day schedule to construct work out plans appropriate to the aspirations and preferences of the user to encompass the claimed portion as Rose utilizes an iterative process, fueled by the trait profile and user inputs, data associated with specific exercises is used to select appropriate and effective exercises and exercise programs from multiple exercise datasets, the identification of appropriate and effective exercises and exercise programs would be prioritized over inappropriate or ineffective exercises. The 35 U.S.C. 103 rejection(s) stand.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Fomin et al. (U.S. Patent Pre-Grant Publication No. 2020/0129808), describes a system and method of predictive analytics that assesses multiple causal factors to a target outcome, determines the relationship and significance of those causal factors to the target outcome, and permits adjustment of a conditioning, wellness and/or athletic training program to more effectively approach or achieve the target outcome.
Shavit (U.S. Patent Pre-Grant Publication No. 2017/0368413), describes a computing device enhanced training environment system comprising a computing device, I/O subsystem for permitting a user to enter at least one attribute of the tmining or of the trainee, a plurality of sensors for generating sensory information, a training environment in which a training activity takes place, a database containing training related information.
Jamil et al. (“Towards Secure Fitness Framework Based on IoT-Enabled Blockchain Network Integrated with Machine Learning Algorithms”), describes a secure fitness framework that is based on an IoT-enabled blockchain network integrated with machine learning approaches.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bennett S Erickson whose telephone number is (571)270-3690. The examiner can normally be reached Monday - Friday: 9:00am - 5:00pm.
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/Bennett Stephen Erickson/Primary Examiner, Art Unit 3683
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