Adaptive Self-Efficacy-Based AI Coaching for Cycling
AI
1 other identifier
interventional
120
1 country
1
Brief Summary
The primary objective of this study is to evaluate whether adaptive, AI-delivered personalized self-efficacy-based AI coaching based on real-time physiological and performance feedback enhance indoor cycling power output during a 20-minute time trial compared to static affirmations and exercise-only control conditions.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for not_applicable
Started Jun 2026
Typical duration for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
December 19, 2025
CompletedFirst Posted
Study publicly available on registry
January 5, 2026
CompletedStudy Start
First participant enrolled
June 1, 2026
ExpectedPrimary Completion
Last participant's last visit for primary outcome
December 23, 2028
Study Completion
Last participant's last visit for all outcomes
December 28, 2028
March 3, 2026
February 1, 2026
2.6 years
December 19, 2025
February 27, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Mean cycling power output during 20-minute time trial
Average cycling power output over the full 20-minute time trial. The outcome compares mean power between intervention arms (adaptive AI coaching vs. static affirmations vs. exercise-only control). Power is captured continuously via the cycling ergometer and summarized as the mean watts for each participant's trial.
Day 2
Study Arms (3)
Control Group
NO INTERVENTIONNo affirmations delivered. Participants receive only time notifications at 5, 10, 15, and 19 minutes for pacing awareness. Same equipment worn to control for potential monitoring effects.
Group 1: Self-efficacy-based AI coaching
EXPERIMENTALThe Thompson Sampling contextual bandit algorithm, trained on Session 1 data, monitors performance continuously and evaluates every 5 seconds whether to deliver an affirmation.
Group 2: Static AI Affirmations
ACTIVE COMPARATORGeneric motivational messages delivered at fixed intervals (minutes 3, 6, 9, 12, 15, and 18) regardless of performance state. Messages follow the same complexity gradient based on elapsed time rather than individual response.
Interventions
The Thompson Sampling contextual bandit algorithm, trained on Session 1 data, monitors performance continuously and evaluates every 5 seconds whether to deliver an affirmation. The policy is trained to maximize a multi-objective "efficacy-preserving performance" function that rewards: * Maintaining target power relative to rolling 30s/2min/5min baselines * Stabilizing short-horizon power variability (30s coefficient of variation) * Stabilizing heart-rate (HR) trajectory consistent with efficient pacing The decision process considers: * Current power relative to 30-second, 2-minute, and 5-minute rolling averages * Power output variability (coefficient of variation over past 30 seconds) * Heart rate trajectory and cardiac drift patterns * Cadence stability and changes from baseline * Time elapsed and expected fatigue progression based on power-duration curve Self-efficacy-based AI coaching adapts to physiological measures (power and heart rate).
Generic motivational messages delivered at fixed intervals (minutes 3, 6, 9, 12, 15, and 18) regardless of performance state. Messages follow the same complexity gradient based on elapsed time rather than individual response: * Minutes 3, 6: "You're building momentum with every pedal stroke-maintain this strong rhythm" * Minutes 9, 12: "Strong effort-push through this challenge" * Minutes 15, 18: "Final push-finish strong"
Eligibility Criteria
You may qualify if:
- Age 18-40 years
- Recreationally active
- Familiar with stationary cycling
- Able to complete 20 minutes of vigorous cycling
You may not qualify if:
- Cardiovascular, metabolic, or respiratory conditions
- Medications affecting heart rate response
- Lower extremity injury within past 3 months
- Competitive cyclists (\>10 hours cycling/week)
- Pregnancy
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
University of Miami
Coral Gables, Florida, 33146, United States
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Anna Queiroz, Ph.D.
University of Miami
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- PARTICIPANT
- Purpose
- BASIC SCIENCE
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Associate Professor
Study Record Dates
First Submitted
December 19, 2025
First Posted
January 5, 2026
Study Start (Estimated)
June 1, 2026
Primary Completion (Estimated)
December 23, 2028
Study Completion (Estimated)
December 28, 2028
Last Updated
March 3, 2026
Record last verified: 2026-02
Data Sharing
- IPD Sharing
- Will not share