Adaptive Self-Efficacy-Based AI Coaching for Cycling

Adaptive Self-Efficacy-Based AI Coaching for Enhanced Indoor Cycling Performance: A Personalized Machine Learning Approach

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.

Inclusion Criteria:

• Age 18-40 years

  • Recreationally active
  • Familiar with stationary cycling
  • Able to complete 20 minutes of vigorous cycling

Exclusion Criteria:

• Cardiovascular, metabolic, or respiratory conditions

  • Medications affecting heart rate response
  • Lower extremity injury within past 3 months
  • Competitive cyclists (>10 hours cycling/week)
  • Pregnancy