Exercise Fatigue Prediction in Healthy Individuals

The goal of this research study is to develop an AI-based model to detect physical fatigue in healthy young adults. The main questions it aims to answer are: 1. Can muscle, heart, and brain signals be used to predict physical fatigue in real time? 2. How accurately can an AI model detect fatigue based on these signals? Participants will: * Perform moderate to high intensity physical exercises, including static bicycling and dumbbell squats, while wearing non-invasive sensors that measure muscle activity (sEMG), heart rate (HR), and brain activity (EEG). * Before starting the exercises, participants will complete a brief warm-up session that includes stretching and mobility movements. * Each participant undergoes two training sessions, with pre- and post-evaluations of their physical fitness status and static muscle strength.

NCT Number	NCT07066462
Lead Sponsor	National Taipei University
Conditions	Healthy Young Adults
Enrollment	17 participants
Start Date	2025-03-01
Primary Completion	2025-08-31 (estimated)
Study Completion	2025-11-30 (estimated)
Updated on ClinicalTrials.gov	2026-04-13