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Personalized Exercise Recommendations for Chronic Pelvic Pain Using Reinforcement Learning

Sponsor: Icahn School of Medicine at Mount Sinai • ClinicalTrials.gov ID: NCT07810218

Registry updated: 2026-09-09

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Description

WorkoutCPP is a pilot study evaluating the feasibility of a personalized exercise recommendation system for individuals with chronic pelvic pain disorders (CPPDs). The study uses reinforcement learning (RL), a type of artificial intelligence that adapts recommendations over time based on each participant's reported pain levels, symptom burden, and exercise compliance. Participants receive daily exercise recommendations that alternate between standard, non-personalized guidance and personalized, RL-generated recommendations across four 2-week phases, allowing within-person comparison of outcomes under each condition. The primary hypothesis is that an RL-based adaptive recommendation system is feasible to deliver in a CPPD population.

Interventions

Reinforcement Learning (RL)-Based Personalized Exercise Recommendations (Behavioral)
Daily exercise recommendations (using type, intensity, and duration) are generated by a contextual bandit reinforcement learning agent, based on the implementation described in Meier et al. 2023. Recommendations are personalized using each participant's initially generated list of exercises based on their physical ability and resources available, as well as contextual daily factors including pain symptoms, prior exercise compliance, and their feedback to the previous exercise recommendation.
Generic Exercise Recommendation (Behavioral)
Participants receive exercise recommendations from a standardized, set list of exercise recommendations that are based on USDHHS physical activity guidelines (Piercy et al., 2020). Recommendations are not personalized based on participant contextual information and do not adapt over the course of the study.

Eligibility criteria

Inclusion criteria: * Self-reported CPPD (e.g., endometriosis, adenomyosis, fibroids, etc.) based on clinician diagnosis * Aged 18-55 years. * Ownership of an iOS or Android smartphone. * Willingness to self-track daily symptoms, exercise activities, and self-management behaviors using a smartphone research app. * Willingness to wear an activity tracker for the study duration. * Willingness to follow exercise recommendations from a smartphone research app, provided no adverse symptoms occur. * Ability to read and write in English sufficient to understand study materials and communications. * At least intermittently physically active (e.g., ≥30 minutes of walking twice per week). Exclusion criteria: * Absolute contraindications to PA (e.g., recent myocardial infarction, complete heart block, acute congestive heart failure, unstable angina, or uncontrolled severe hypertension, BP ≥180/110 mm Hg). * More than two "Yes" responses on the Physical Activity Readiness Questionnaire (PAR-Q) (16) without physician clearance. * Major life events expected during the next 10 weeks (e.g., pregnancy, planned surgery, or extended travel likely to interfere with participation). * Current or planned pregnancy within the next 6 months. * Having given birth in the past 6 months or currently nursing. * Inability to wear an activity tracker or use the app for the study duration. * Complete inactivity (i.e., \<60 minutes of moderate-intensity PA per week).

Conditions

Pelvic Pain Endometriosis Chronic Pelvic Pain

Locations

Icahn School of Medicine at Mount Sinai — New York, New York, United States

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Official Source

Data sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.

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