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 Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 2, 4, 6-9, 11, 13-16, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Belson (US Patent No. 11,701,546) in view Asikainen (U.S. PGPUB 2022/0296966).
Re claims 1, 8, and 15: Belson discloses with respect to a method for generating a workout plan, the method comprising:
accessing training data comprising information describing, for each historical user of a population of historical users, characteristics of the historical user and strength data representative of a measure of strength of the historical user over time (Abstract & column 7, lines 42-55: “The 1 eRM is the force at a speed of approximately zero in an FVP. The FVP relationship is based on data collected from many users for each movement, as the relationship varies for each different movement.” and “The predetermined FVP, or strength typing, may be established using a pool of users who perform the given movement one or more times and using linear regression and/or other statistical modeling techniques, including, for example, a higher order polynomial-based statistical analysis;”);
training a machine-learned model using the accessed training data, the machine-learned model configured to predict a future measure of strength for a user based on characteristics of the user (Abstract & column 17, lines 27-45: the machine-learned model uses the training data for thousands of historical reps by the users, to predict a ROM, i.e. measure of strength, for the next rep) ;
applying the machine-learned model to characteristics of a target user to predict, for each of a plurality of future times, a measure of strength of the target user at the future time (Abstract & column 17, lines 27-45: the system predicts the ROM for each rep);
determining that an actual measure of strength of the target user at a first future time is less than a predicted measure of strength of the target user corresponding to the first future time (Abstract & column 21, lines 63-67: “In step (306), a failure classification of whether the one or more upcoming repetitions is associated with an occurrence of physical failure is performed based at least in part on the predicted performance of the one or more upcoming repetitions of the exercise movement.”);
and modifying a workout for the target user based on a muscle or muscle group associated with the predicted measure of strength (column 14, lines 12-31: the weight is therefore lowered on subsequent repetitions).
Belson fails to disclose “displaying the predicted measure of strength of the target user at the first future time within an application interface.” However, Asikainen discloses a machine based learning system that operates an interactive personal training device whereby the system displays a predicted measure of strength and a future time when such will be achieved in both a graph and through a message directly to the user (see Fig. 11, object 1103; see Fig. 13, object 1303). It would have been obvious to one of ordinary skill in the art at the time the invention was filed, to modify the display of Belson with the displayed predicted measure of strength and when such would occur, as taught by Asikainen for the purpose of informing the user when they will accomplish specific goals.
Re claim 2, 9, 16: Belson discloses with respect to the method of claim 1, wherein the characteristics comprise one or more of: maximum weight single repetition exercises that a user can perform, community results based on a population of people with one or more characteristics in common with the user, demographic information associated with the user, and health metric information associated with the user (see column 7, lines 31-41: “The machine determines user's strength level from at least
one and practically with 3-4 isokinetic seed movements on the machine. The force and speed time series data stored during the reps may be used to find the 1 eRM the user could perform at each movement”).
Re claim 4, 11, and 18: Belson in view of Asikainen discloses with respect to the method of claim 3, wherein the display within the application interface includes a trendline including a plurality of future times (see Asikainen, see Fig. 11, object 1103). It would have been obvious to one of ordinary skill in the art at the time the invention was filed, to modify the display of Belson with the displayed predicted measure of strength and when such would occur, as taught by Asikainen for the purpose of informing the user when they will accomplish specific goals.
Re claim 6, 13, and 20. Belson in view of Asikainen discloses with respect to the method of claim 5 wherein the displayed trendlines include an overlay with an actual measure of strength of the target user over time. (see Asikainen, see Fig. 11, object 1103). It would have been obvious to one of ordinary skill in the art at the time the invention was filed, to modify the display of Belson with the displayed predicted measure of strength and when such would occur, as taught by Asikainen for the purpose of informing the user when they will accomplish specific goals.
Re claim 7 and 14: Belson in view of Asikianen discloses with respect to the method of claim 1, wherein modifying a workout for the target user further comprises adding exercises associated with the muscle or muscle group (see Asikianen, see paragraph [0113, 0116]: “Examples of adaptive training changes recommended for the next workout session may include, but are not limited to, increase or decrease in volume or weight, type of workout to target muscle groups undertrained, automatic reduction in sets and/or repetitions of exercise movements for muscle groups overtrained, temporary removal of exercises for muscle groups overtrained, type of workout targeting antagonist muscles, increase in mobility or recovery based exercises and stretches for muscle groups overtrained, recently trained, or for a future target fitness goal.” [0124]: discussing adding deeper squats, see Fig. 13, object 1303: discussing repetitions with more eccentric load time). It would have been obvious to one of ordinary skill in the art at the time the invention was filed, to modify the coaching system of Belson with exercises modification and addition feature of Asikianen, for the purpose of aiding the user in better reaching their goal.
Allowable Subject Matter
Claims 5, 12, and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 2, 4, 6-9, 11, 13-16, 18, and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Upon a further search, the newly found art of Asikianen discloses previously indicated allowed claims, and thus the previous rejection was been withdrawn.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REGINALD A RENWICK whose telephone number is (571)270-1913. The examiner can normally be reached Monday-Friday 11am-7pm.
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REGINALD A. RENWICK
Primary Examiner
Art Unit 3714
/REGINALD A RENWICK/Primary Examiner, Art Unit 3715
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