[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100578920":3},{"organization":4,"armGroups":7,"interventions":25,"overallOfficials":30,"centralContacts":38,"locations":30,"responsibleParty":48,"collaborators":30,"id":52,"slug":53,"hasResults":54,"nctId":55,"briefTitle":56,"officialTitle":57,"acronym":30,"eligibilityCriteria":58,"healthyVolunteers":54,"sex":59,"minAge":60,"maxAge":30,"enrollmentInfo":61,"targetDuration":30,"studyType":64,"phases":65,"briefSummary":67,"conditions":68,"keywords":73,"overallStatus":75,"whyStopped":30,"lastUpdateSubmitDate":76,"lastUpdatePostDateStruct":77,"startDateStruct":80,"completionDateStruct":82,"leadSponsor":84,"locationsCount":30},{"fullName":5,"class":6},"National Defense Medical Center, Taiwan","OTHER",[8,14,19],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-PEF","EXPERIMENTAL","the AI-PEF group, receiving a machine learning-powered personalized exercise program.",[13],"Behavioral: AI-PEF",{"label":15,"type":10,"description":16,"interventionNames":17},"Theory-based digital exercise","Theory-based digital exercise group, engaging in structured digital exercise without machine learning- powered feedback.",[18],"Behavioral: Theory-based digital exercise",{"label":20,"type":21,"description":22,"interventionNames":23},"Active control group","ACTIVE_COMPARATOR","the Active control group, receiving general exercise recommendations as part of standard care in a 1:1:1 ratio.",[24],"Behavioral: Active Control",[26,31,34],{"type":27,"name":9,"description":28,"armGroupLabels":29,"otherNames":30},"BEHAVIORAL","Participants will follow a 12-week walking program with five 30-minute sessions per week, progressively increasing intensity based on heart rate and effort indices. Garmin fitness trackers will monitor adherence and intensity. Remote guidance will support participants via weekly digital health messages on the LINE app, offering personalized feedback, goal reinforcement, and lifestyle recommendations. Participants will also receiThese AI feedback implementations will be tailored to complement the in-person education and will include reminders of the individualized goals set during the remote exercise intervention and consultation . The digital component will also offer a platform for patients to share their progress and seek further guidance during the scheduled in-person consultation. The use of digital AI feedback aligns with the trend of integrating technology into healthcare services, providing a convenient and accessible modality for supporting parents engaging in regular exercise.",[9],null,{"type":27,"name":15,"description":32,"armGroupLabels":33,"otherNames":30},"The theory-based digital exercise group will follow the same in-person clinic visits and walking program as AI-PEF but without AI-driven feedback",[15],{"type":27,"name":35,"description":36,"armGroupLabels":37,"otherNames":30},"Active Control","Participants in the active control group will receive standard TBI care, including Garmin-based self-monitoring and routine clinic visits at baseline (T0), 3 months (T1), and 6 months (T2). These visits will include general health education and recommendations on daily physical activity. No personalized or digital exercise strategies will be provided. Participants completing the 6-month protocol will have the option to access the AI-PEF program after the study.",[20],[39,45],{"name":40,"role":41,"phone":42,"phoneExt":43,"email":44},"Hui-Hsun Chiang, Professor","CONTACT","886-2-87923100","18761","sheisvivian@gmail.com",{"name":40,"role":41,"phone":46,"phoneExt":30,"email":47},"886-921060383","huihsunchiang@mail.ndmctsgh.edu.tw",{"type":49,"investigatorFullName":50,"investigatorTitle":51,"investigatorAffiliation":5,"oldNameTitle":30,"oldOrganization":30},"PRINCIPAL_INVESTIGATOR","Hui-Hsun Chiang","Professor","100578920","ai-driven-personalized-exercise-feedback-program-on-exercise-adherence-in-traumatic-brain-injury-100578920",false,"NCT06817564","AI-driven Personalized Exercise Feedback Program on Exercise Adherence in Traumatic Brain Injury","Effects of an AI-driven Personalized Exercise Feedback Program on Exercise Adherence and Health Outcomes in Patients with Traumatic Brain Injury","Inclusion Criteria:\n\n* Eligible participants are patients aged over 18 with mild TBI (GCS 13-15)\n* who can walk independently,\n* reside in the Greater Taipei area,\n* and possess sufficient Chinese or Taiwanese language proficiency to understand the trial\n* complete self-administered questionnaires.\n\nExclusion Criteria:\n\n* Exclusion criteria include individuals with severe medical conditions (e.g., respiratory failure, epilepsy, psychiatric disorders), musculoskeletal or neurological impairments\n* hindering physical activity in the 6-minute walk test,\n* cognitive impairments (MMSE \\\u003C 24),\n* frontal lobe injuries or penetrating injury causing significant psychological dysfunction.\n* Patients regularly engaging in moderate-to-high-intensity aerobic exercise or participating in other studies will also be excluded to avoid bias.","ALL","18 Years",{"count":62,"type":63},125,"ESTIMATED","INTERVENTIONAL",[66],"NA","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.\n\nMethods: 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 adherence, sleep quality, depressive symptoms, and quality of life with 90 participants in a 3-arm randomized trial.",[69,70,71,72],"Traumatic Brain Injury","Exercise","AI (Artificial Intelligence)","Digital Health",[74],"AI-Driven Personalized Exercise Program","NOT_YET_RECRUITING","2025-02-08",{"date":78,"type":79},"2025-02-12","ACTUAL",{"date":81,"type":63},"2025-03-01",{"date":83,"type":63},"2031-08-31",{"name":5,"class":6}]