Prosecution Insights
Last updated: April 19, 2026
Application No. 18/491,479

USER EXPERIENCE PLATFORM FOR CONNECTED FITNESS SYSTEMS

Non-Final OA §102
Filed
Oct 20, 2023
Examiner
KENNEDY, JOSHUA T
Art Unit
3784
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Peloton Interactive, Inc.
OA Round
1 (Non-Final)
51%
Grant Probability
Moderate
1-2
OA Rounds
2y 8m
To Grant
99%
With Interview

Examiner Intelligence

Grants 51% of resolved cases
51%
Career Allow Rate
689 granted / 1348 resolved
-18.9% vs TC avg
Strong +48% interview lift
Without
With
+48.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
42 currently pending
Career history
1390
Total Applications
across all art units

Statute-Specific Performance

§101
1.4%
-38.6% vs TC avg
§103
39.5%
-0.5% vs TC avg
§102
33.1%
-6.9% vs TC avg
§112
22.7%
-17.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1348 resolved cases

Office Action

§102
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 . Election/Restrictions Claims 12-16 and 19-20 have been withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim.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 10/1/2025. Claims 1-11, 17, and 18 have been examined. 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 1-11, 17, and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Askikainen et al (WO 2021007581). 1. Askikainen et al disclose a connected fitness system, comprising: a media hub (204) that captures images of a user performing a workout and presents content to the user via a user interface associated with the media hub (Par. 0072); a classification system that classifies poses or exercises performed by the user from the images captured by the media hub (Par. 0069-0082); and a body focus system (210) that generates content to be presented to the user via the user interface, wherein the content is generated based on classifications of the poses or exercises performed by the user (Par. 0089-0093. 2. Askikainen et al disclose one or more computer memories that store a data structure associated with connected fitness information to be presented to a user of an exercise machine, the data structure including one or more entries, where each of the entries includes: information identifying a movement to be performed by a user during an exercise activity (Par. 0071); and metadata associated with the movement to be performed by the user during the exercise activity (Par. 0073-0074). 3. Askikainen et al disclose the one or more computer memories of claim 2, wherein the movement is a unit of a class presented to the user during the exercise activity (Par. 0071). 4. Askikainen et al disclose the one or more computer memories of claim 2, wherein the movement is an atomic unit of a class presented to the user during the exercise activity (Par. 0071). 5. Askikainen et al disclose the one or more computer memories of claim 2, wherein the metadata associated with the movement to be performed by the user during the exercise activity includes context information for the movement that identifies a body part or muscle group associated with the movement (Par. 0074). 6. Askikainen et al disclose the one or more computer memories of claim 2, wherein the metadata associated with the movement to be performed by the user during the exercise activity includes context information for the movement that identifies a description of the movement (Par. 0080). 7. Askikainen et al disclose the one or more computer memories of claim 2, wherein the metadata associated with the movement to be performed by the user during the exercise activity includes context information for the movement that identifies an exercise machine or exercise equipment associated with the movement (Par. 0081). 8. Askikainen et al disclose the one or more computer memories of claim 2, wherein the metadata associated with the movement to be performed by the user during the exercise activity includes an identifier that represents a machine learning algorithm associated with tracking the movement when the movement is performed by the user during the exercise activity (Par. 0076-0077). 9. Askikainen et al disclose the one or more computer memories of claim 2, wherein the metadata associated with the movement to be performed by the user during the exercise activity includes information that identifies related movements (Par. 0080). 10. Askikainen et al disclose the one or more computer memories of claim 2, wherein the metadata associated with the movement to be performed by the user during the exercise activity includes information that identifies variations to the movement (Par. 0083-0084). 11. Askikainen et al disclose the one or more computer memories of claim 2, wherein the metadata associated with the movement to be performed by the user during the exercise activity includes information that identifies content stored in a movement library that is associated with the movement (Par. 0069). 17. Askikainen et al disclose the connected fitness system of claim 1, wherein the classification system includes: a classification network that classifies the poses or exercises performed by the user from the images captured by the media hub (Par. 0069 and 0079); and a match network that matches the poses or exercises performed by the user during the workout to a template to determine a match prediction for the poses or exercises depicted in images captured by the media hub (Par. 0080). 18. Askikainen et al disclose the connected fitness system of claim 1, wherein the classification system comprises a machine learning classification network, including: a series of encoding layers and decoding layers to generate a predicted keypoint heatmap for the images as a feature map for the images (Par. 0077); and additional downsampling layers and a Softmax function that generate a pose classification or exercise classification from the feature map (Par. 0068-0071, 0077-0078). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Askikainen et al, Shavit, Mehl et al, Fralick et al, and Leroyer et al all disclose similar exercise systems and methods for monitoring and evaluating body movements to provide feedback to a user. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSHUA T KENNEDY whose telephone number is (571)272-8297. The examiner can normally be reached M-F 7a-4:30p MST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, LoAn Jimenez can be reached at (571) 272-4966. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JOSHUA T KENNEDY/Primary Examiner, Art Unit 3784 10/8/2025
Read full office action

Prosecution Timeline

Oct 20, 2023
Application Filed
Oct 08, 2025
Non-Final Rejection — §102 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12594453
WEIGHT-ADJUSTABLE DUMBBELL
2y 5m to grant Granted Apr 07, 2026
Patent 12589271
DEVICE FOR PERFORMING PHYSICAL EXERCISES, IN PARTICULAR FOR MOTOR REHABILITATION EXERCISES
2y 5m to grant Granted Mar 31, 2026
Patent 12582866
EXERCISE BENCH WITH SIDE PADS
2y 5m to grant Granted Mar 24, 2026
Patent 12576300
Assisted Planche Exercise Apparatus
2y 5m to grant Granted Mar 17, 2026
Patent 12576327
EXERCISE BENCH WITH INTEGRATED WEIGHT STORAGE UNIT
2y 5m to grant Granted Mar 17, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
51%
Grant Probability
99%
With Interview (+48.0%)
2y 8m
Median Time to Grant
Low
PTA Risk
Based on 1348 resolved cases by this examiner. Grant probability derived from career allow rate.

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