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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/9/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Election/Restrictions
Claims 15-20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 12/23/2025.
Claim Rejections - 35 USC § 102
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 1-14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Burroughs et al. (US Patent Pub. 20170014684; referred to hereinafter as Burroughs).
Claim 1: Burroughs disclose a method of determining an event participated in by an athlete (0004-0005), the method comprising, receiving, at a computing device, a plurality of motion determinations generated based on motion data captured from motion data of the athlete during a monitoring window (0052), wherein the motion determinations comprise at least one of an action performed by the athlete and performance metrics of the athlete (0076-0081), classifying, by use of a machine learning model stored on the computing device and based on the motion determinations, an event based at least in part on the plurality of motion determinations, wherein the event represents a classification of the plurality of motion occur determinations (0082, 0086-0087), generating a graphical user interface visualizing the event in relation to a time-related parameter (0091-0095, performance metrics that are tracked and displayed).
Claim 2: Burroughs disclose generating, by the computing device, a timeline of events participated in by the athlete based at least in part on a set of motion determinations comprising the plurality of motion determinations by applying the machine learning model to the set of motion determinations (0090 & 0095).
Claim 3: Burroughs disclose generating the timeline of events comprises classifying individual motion determinations among the plurality of motion determinations as being generated from motion data captured during individual events among the timeline of events (0095-0180 which includes classifying motion such as jumping, running etc. associated with sports).
Claim 4: Burroughs disclose before the receiving step, training the machine learning model to identify events athletes participate in by submitting training timelines to the machine learning model, and each training timeline comprises a plurality of sample motion determinations and indications of when sample events occurred (0099, 0127-0129, provides sample motion event occurred and calibration to allow the system to ‘learn’).
Claim 5: Burroughs disclose wherein the indications of when sample events occurred include event type tags associated with sample motion determinations among the plurality of sample motion determinations (figs. 30A-C and 0130-0132).
Claim 6: Burroughs disclose generating an unfiltered timeline of events participated in by the athlete based in part on the set of motion determinations by applying the machine learning model to the set of motion determinations; and filtering the unfiltered timeline of events by changing start times of individual events within the timeline of events to comply with filtering rules (0156).
Claim 7: Burroughs disclose wherein the filtering rules comprise possible durations for events among a plurality of predetermined events (0156, provides multiple filtering processes).
Claim 8: Burroughs disclose wherein the plurality of predetermined events comprises exercise, training for a sport, and a match of the sport (0106 & 0127-0129).
Claim 9: Burroughs disclose creating a plurality of test motion determinations based on motions of a test athlete during a test window, using the machine learning model to output a test event classification of which event among the plurality of predetermined events the test athlete participated in during the test window based on the plurality of test motion determinations (0052 & 0070-0082), and correcting the test event classification based on a record of what event the test athlete participated in during the test window (0092-0096, correcting or updating event the test athlete participated).
Claim 10: Burroughs disclose determining, by the computing device, a role of the athlete in a team sport based at least in part on the plurality of motion determinations by applying the machine learning model to the plurality of motion determinations (0110).
Claims 11-12: Burroughs disclose any one or any combination of a kick, a step, dribbling a ball, and running, and furthermore any one or any combination of distance traveled, travel speed, and kick force (0082).
Claim 13: Burroughs disclose event among a plurality of predetermined events the athlete participated in during the monitoring window is further based on video footage of the athlete during the monitoring window (0057).
Claim 14: Burroughs disclose creating tagged footage by tagging training video footage of athletes participating in events among the plurality of predetermined events with start times of the events among the plurality of predetermined events (0100-0101) and training the machine learning model on the tagged footage to recognize participation in the events among the plurality of predetermined events (0102-0106).
Examiner’s Note
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Crowley (9,218,418) refers to a computer-implemented athletic performance analysis method that includes obtaining, at a computer system, first motion data reflecting motion of a sporting device during one or more drills performed by an athlete. The method also includes creating and storing action data by identifying a plurality of portions of the motion data, where each of the portions correspond to one or more actions by the athlete; comparing the action data for the athlete, with the computer system, to corresponding aggregated action data for a plurality of other athletes to determine a relative skill level for the athlete with respect to the one or more actions; and generating data for a report that reflects the relative development level of the athlete.
Wiebe (20180140902) refers to exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.
The referenced citations made in the rejection(s) above are intended to exemplify areas in the prior art document(s) in which the examiner believed are the most relevant to the claimed subject matter. However, it is incumbent upon the applicant to analyze the prior art document(s) in its/their entirety since other areas of the document(s) may be relied upon at a later time to substantiate examiner's rationale of record. A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert. denied, 469 U.S. 851 (1984). However, "the prior art's mere disclosure of more than one alternative does not constitute a teaching away from any of these alternatives because such disclosure does not criticize, discredit, or otherwise discourage the solution claimed ...." In re Fulton, 391F.3d 1195, 1201,73 USPQ2d 1141, 1146 (Fed. Cir. 2004).
Conclusion
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/SUNIT PANDYA/Primary Examiner, Art Unit 3715