AI-driven Personalized Exercise Feedback Program on Exercise Adherence in Traumatic Brain Injury

This study aims to develop and evaluate an AI-driven Personalized Exercise Feedback Program (AI-PEF) to enhance exercise adherence and health outcomes in mTBI patients. Methods: AI-PEF integrates the transtheoretical model and self-determination theory with machine learning algorithms to provide real-time, personalized feedback. A phased randomized controlled trial will be conducted: Phase I evaluates feasibility and acceptability through Delphi methods with expert consensus and patient feedback; Phase II validates preliminary outcomes with 30 participants in a 2-arm randomized trial; and Phase III assesses the program's impact on exercise adherence, exercise motivation, mHealth app usability, functional capacity, sleep quality, depressive symptoms, concussion symptoms, and quality of life with 90 participants in a 3-arm randomized trial. In Phase III, quantitative and qualitative data will be collected in parallel, with qualitative data collected through semi-structured interviews to explore participants' experiences and perceptions of the intervention.

Inclusion Criteria: * Eligible participants are patients aged over 18 with mild TBI (GCS 13-15) * who can walk independently, * reside in the Greater Taipei area, * and possess sufficient Chinese or Taiwanese language proficiency to understand the trial * complete self-administered questionnaires. Exclusion Criteria: * include individuals with severe medical conditions (e.g., respiratory failure, epilepsy, psychiatric disorders), musculoskeletal or neurological impairments * hindering physical activity in the 6-minute walk test, * cognitive impairments (MMSE \< 24), * frontal lobe injuries or penetrating injury causing significant psychological dysfunction. * Patients regularly engaging in moderate-to-high-intensity aerobic exercise or participating in other studies will also be excluded to avoid bias.