AI (Artificial Intelligence), Digital Health, Exercise, Traumatic Brain Injury
Conditions
Keywords
AI-Driven Personalized Exercise Program
Brief summary
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.
Detailed description
The study will employ a stepwise, multi-phase design, combining a two- parallel-group pilot study and a three-arm randomized controlled trial (RCT) to evaluate the appropriateness, feasibility, acceptability, and effectiveness of the AI-PEF (Figure 5). Participants will be recruited from the neurosurgery clinics at Tri-Service General Hospital, Taipei. Recruitment will be facilitated through referrals by attending physicians and registered nurses, who will be briefed on the study protocol. Study procedures 1. Phase I (Year 1): Development and Pilot Testing (Aim 1) Phase I will focus on developing and refining the AI-PEF through expert validation and pilot testing. This phase will use a sequential-parallel hybrid design to develop and evaluate the appropriateness of the AI-PEF to deliver personalized exercise empowerment. Stage 1, Delphi Process for AI-PEF Development: Ten experts from diverse fields will participate in two Delphi rounds to finalize the AI-PEF framework. This includes refining algorithms, educational materials, and preliminary validation of key components, such as personalization algorithms and behavior-change strategies. Stage 2, Small-Scale Pilot Study (Early Feedback): A single-arm pilot study with 5 patients will be conducted over four weeks to gather feedback on usability, engagement, and content clarity. 2. Phase II : Larger Pilot Study (Aim 2) Phase II will focus on evaluating the feasibility, acceptability, and preliminary effectiveness of the refined AI-PEF intervention. A two-parallel-group design will be employed, with 30 participants, 15 participants per group, randomly assigned in a 1:1 ratio to the AI-PEF group and Active control group. Over three months, AI-PEF participants will engage in personalized exercise guided by AI, while active control participants will follow standard exercise recommendations. Both qualitative and quantitative data will be collected. Assessments will occur at baseline (T0) and 3 months (T1), including fitness tracker data, questionnaires (motivation, sleep, symptoms), and semi-structured interviews. The primary outcome of interest will be adherence rates, while secondary outcomes will focus on motivation and various health metrics. 3. Phase III : Full- scale three-arm RCT (Aim 3) Phase III will assess the long-term impact of the AI-PEF on exercise adherence, motivation, and health outcomes through a 3-arm RCT, in which participants will be randomly assigned in a 1:1:1 ratio to one of three groups: (1) the AI-PEF group, receiving a machine learning-powered personalized exercise program; (2) the Theory-based digital exercise group, engaging in structured digital exercise without machine learning-powered feedback; or (3) the Active control group, receiving general exercise recommendations as part of standard care. Participants will receive group-specific interventions during the 12-week intervention period and will be followed for six months, with assessments conducted at baseline (T1), 1 month (T2), 2 months (T3), 3 months (T4), and the 6-month follow-up (T5). Primary outcomes will include exercise adherence, exercise motivation, mHealth app usability, and functional capacity. Exercise adherence will be objectively measured via Garmin fitness trackers; exercise motivation and mHealth app usability will be assessed through standardized questionnaires; and functional capacity will be evaluated using the 6-Minute Walk Test. Secondary outcomes, such as sleep quality, depressive symptoms, concussion symptoms, and quality of life, will also be assessed through standardized questionnaires. These standardized questionnaires are being used in our current digital remote exercise trial in patients with mild TBI (NSTC 112-2314-B-016-007-MY2) and have demonstrated good psychometric performance. Quantitative and qualitative data will be collected and analyzed in parallel.Quantitative data will be used to compare adherence, motivation, usability, functional capacity, and health outcomes across the three groups and to evaluate the efficacy of AI-PEF relative to standard interventions. Qualitative interviews will explore participants' experiences and perceptions of the intervention. Procedures will adhere to the blinding and randomization protocols described in Intervention Fidelity, ensuring unbiased assignment and data collection processes. This proposed study protocol is closely aligned with those that have been successfully implemented in our previous digital exercise trial.
Interventions
BEHAVIORALAI-PEF
Participants will follow a 12-week walking program with at least three 30-minute sessions per week, with exercise intensity progressively adjusted based on heart rate and effort indices. Garmin fitness trackers will monitor exercise adherence and intensity. Remote guidance will be provided through five AI-generated digital health messages per week via LINE, delivered on Monday, Tuesday, Thursday, Friday, and Saturday, and tailored to participants' exercise performance and individualized goals established during the remote exercise intervention and consultation. The messages will include exercise performance feedback, goal setting and reinforcement, exercise and device-use reminders, health education, and encouragement and support. The digital component will allow participants to share their progress and seek guidance during scheduled in-person consultations. AI-driven digital feedback provides a convenient and accessible approach to supporting participants in engaging in exercise.
BEHAVIORALTheory-based digital exercise
The theory-based digital exercise group will follow the same in-person clinic visits, assessment schedule, and 12-week walking program as the AI-PEF group. Garmin fitness trackers will be used to monitor exercise adherence and intensity. The research team will deliver five standardized digital health messages per week through the LINE app using message templates developed in advance. The messages will include exercise guidance, goal setting and reinforcement, exercise and device-use reminders, health education and lifestyle recommendations, and encouragement and support. The messages will not be generated or tailored by AI, and participants will not receive AI-driven personalized feedback.
BEHAVIORALActive Control
Participants in the active control group will receive standard TBI care, including routine clinic visits. In addition, Garmin fitness trackers will be provided for self-monitoring during the study. The research team will deliver five standardized general health messages per week through the LINE app. The messages will include TBI-related health education, general health and lifestyle information, general recommendations for daily physical activity, general check-in messages, and technical reminders for Garmin use. The messages will not include structured exercise guidance, individualized goal setting or reinforcement, performance-based feedback, or AI-generated personalized feedback. Participants completing the 6-month protocol will have the option to access the AI-PEF program after the study.
Sponsors
National Defense Medical Center, Taiwan
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
DOUBLE (Subject, Outcomes Assessor)
Masking description
Physicians are masked.
Intervention model description
Phase 2: Evaluate the feasibility, acceptability, and preliminary effectiveness of the AI-PEF in improving patient outcomes. Phase 3: Examine the impact of the AI-PEF on exercise adherence and health outcomes
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Adherence | T1-baseline | Exercise adherence will be defined as the percentage of prescribed sessions completed during the 12-week intervention, based on three 30-minute sessions per week (36 sessions in total). The Garmin Vivosmart 5 will record exercise frequency, duration, and intensity. A session will be considered completed when the participant exercises for at least 30 minutes and reaches Garmin heart rate zone 2 or higher. Adherence will be calculated by summing completed sessions, with a maximum of three sessions counted per week, dividing by 36, and multiplying by 100. Scores range from 0% to 100%, with higher percentages indicating greater adherence. Borg Rating of Perceived Exertion (RPE) will complement intensity assessment, particularly for older participants or those with heart rate or blood pressure concerns. An RPE of ≥12 indicates moderate intensity, while ≥11 may be encouraged initially, followed by gradual progression as tolerated. |
| The Chinese Version of the Sport Motivation Scale-II | T1- baseline | The Chinese version of the Sport Motivation Scale-II (CSMS-II) will be used to assess six types of motivation: intrinsic motivation, integrated regulation, identified regulation, introjected regulation, external regulation, and amotivation. The scale consists of 18 items rated on a 7-point Likert scale from 1 to 7. The subscales include intrinsic motivation (items 3, 9, and 17), integrated regulation (items 4, 11, and 14), identified regulation (items 6, 12, and 18), introjected regulation (items 1, 7, and 16), external regulation (items 5, 8, and 15), and amotivation (items 2, 10, and 13). Each subscale is scored separately by calculating the mean of its three items. Each subscale score ranges from 1 to 7, with higher scores indicating a stronger level of the corresponding motivational regulation. |
| The mHealth App usability questionnaire | T1- baseline | The Mobile App Usability Questionnaire (MAUQ) assesses usability across three dimensions: usability and satisfaction, system information arrangement, and system efficiency. A Chinese version of the questionnaire was developed in 2022, with an internal consistency reliability (Cronbach's α) of 0.988 and an internal consistency range of 0.845-0.931. The test-retest reliability ranges from 0.828 to 0.918. A total of 21 items, Likert scale scores ranged from 1 (strongly agree) to 7 (strongly disagree), indicating the lower scores the better usability. |
| 6-Minute Walk Test | T1- baseline | Functional capacity will be evaluated using the 6-Minute Walk Test (6MWT), which measures the distance walked in six minutes as an indicator of functional exercise capacity. A longer walking distance indicates better functional capacity. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| The Rivermead Post-Concussion Symptoms Questionnaire | T1- baseline | The Rivermead Post-Concussion Symptoms Questionnaire (RPQ) will assess physical, cognitive, and behavioral symptoms associated with TBI, validated for mild to moderate TBI cases. A total of 16 items, scored 0-4, ranged 0- 64, the higher scores mean the severity of the concussion symptoms. |
| The Beck Depression Inventory-II | T1- baseline | The Beck Depression Inventory-II (BDI-II), with total scores categorized as follows: 0-13 (normal), 14-19 (mild depression), 20-28 (moderate depression), and 29-63 (severe depression), will evaluate depressive symptoms with established reliability (α = 0.94) and validity. |
| The Pittsburgh Sleep Quality Index | T1-baseline | The Pittsburgh Sleep Quality Index (PSQI) will assess subjective sleep quality, using a validated Chinese version. Previous research has demonstrated good internal consistency reliability (0.82) and 14- to 21-day test-retest reliability (0.85) of the PSQI Chinese version in Taiwan's populations. Each component score of the PSQI ranges from 0 to 3, with 3 indicating the greatest dysfunction or disturbance. The seven component scores are then summed to obtain a global PSQI score, which ranges from 0 to 21. Higher scores indicate poorer sleep quality, with a score greater than 5 suggesting significant sleep difficulties. |
| The Godin-Shephard Leisure Time Physical Activity Questionnaire | T1 -baseline | The Godin-Shephard Leisure Time Physical Activity Questionnaire (GLTPA) will measure weekly physical activity intensity, classified into light, moderate, and vigorous levels. The Chinese version of the GLTPA has shown good validity and is significantly correlated with mental health outcomes. By classifying physical activity intensity lasting for more than 15 minutes in the past week into strenuous activities, moderate strenuous activities, and light activities, and then multiplying by corresponding coefficients 9, 5, and 3 respectively for quantification, the sum of these scores is Godin's leisure time physical Total activity score, with higher scores indicating greater physical activity. The level of physical activity can be divided into three levels according to the total Godin leisure time physical activity score. A total score of 24 or above is considered active, a score between 14 and 23 is moderately active, and a score below 14 is consider Insufficiently active. |
| The World Health Organization Quality of Life Scale-brief | T1 - baseline | The World Health Organization Quality of Life Scale-brief (WHOQOL-BREF), validated in Chinese, with good internal consistency (α = 0.70-0.77), overall reliability (α = 0.91), and test-retest reliability (0.76-0.80), will assess the quality of life across four domains: physical, psychological, social, and environmental well-being. This scale covers subjective life feelings in four major categories: physical health, psychological, social relations, and environment. It has 24 questions in total. There are also 2 questions measuring the overall quality of life and general health at the general level. (general health), in addition, the Taiwan version adds 2 local questions, namely diet (whether you can eat the food you want) and face issues (whether you are respected), a total of 28 questions, and the scores for each category are introduced. Between 4 and 20, the higher the score, the better the quality of life. |
| Mini-Mental State Examination | T1- baseline | Cognitive function will be assessed pre-enrollment using the MMSE, with validated age- and education-adjusted thresholds. The MMSE has demonstrated good reliability and validity and is a strong predictor of disability levels in patients with traumatic brain injury. Participants with an MMSE score below 24 will be excluded from the study to ensure appropriate cognitive capacity for participation. The score range is 0-30 points, with the international standard cut-off value of 24 points, 18-24 points as mild dementia, 16-17 points as moderate dementia, and ≦15 points as severe dementia. |
| Montreal Cognitive Assessment | T1-baseline | The Montreal Cognitive Assessment (MoCA) is a sensitive tool for the early screening of mild cognitive impairment, particularly useful for detecting deficits in executive function, attention, short-term memory, language fluency, abstract thinking, and visuospatial abilities. The total score of the scale is 30 points, with a score of less than 26 considered indicative of possible mild cognitive impairment. The score can be adjusted (+1 point) based on educational level. The Chinese version of MoCA has been proven to have good reliability and validity (Cronbach's α = 0.83) and is particularly suitable for research populations in Asian regions. |
| Near-Infrared Brain Blood Flow Imaging | T1 - baseline | In this study, the Biolight MediTECH® near-infrared brain blood flow imaging sensor (hemoencephalography; HEG) was used to measure blood flow in the prefrontal cortex. The Biolight near-infrared spectroscopy device is an HEG sensor designed by MediTECH®, based on NIR technology to observe the optical properties of cells and tissues at the reflection level. This enables monitoring of changes in oxyhemoglobin and deoxyhemoglobin concentrations. By measuring light absorption at different wavelengths, the system can continuously track changes during tissue oxidation processes, thereby measuring cerebral blood flow conditions. The percentage of the NIR brain blood flow ranged 0- 100%, the higher percentage means the higher prefrontal brain blood flow. |
| cardiac metabolic performance benchmark | T1- baseline | Preliminary findings from this study applied the cardiac metabolic performance benchmark (CMPB3) to compare the effectiveness of increasing cerebral blood circulation at different intensities (CMPB3 ≤ 35, 40, 45, 50). Results indicated that CMPB3 levels above 40 effectively increased cerebral blood circulation, with improvements observed not only during exercise but also during the post-exercise rest period, where cerebral blood flow remained higher than the baseline level. The lower intensity means the lower exercise intensity and the higher ability to perform aerobic walking exercise. The benchmark will be calculated by the Heart rate measured by Garmin fitness bracelet. |
| Semi-Structured Interviews | T1- baseline | This study will adopt semi-structured interviews to gain an in-depth understanding of participants' experiences and perceptions of the walking program, as well as to complement and interpret quantitative data. It is a qualitative data, not a quantitative data. The interview content covers three major themes: 1. Benefits of the walking program; 2. Experiences and challenges of the walking program; 3. The impact of the walking program on quality of life, sleep quality, concussion symptoms, psychological resilience, depression, exercise motivation, exercise self-efficacy, and physical activity. |
| Physiological Monitoring Tools | T1- baseline | Garmin Vivosmart 5. This wearable device will track heart rate, exercise frequency, exercise duration, exercise intensity, step count, and sleep data. Data will be integrated with the Garmin Connect app for real-time monitoring and feedback. A preliminary study conducted by our research team in 2020 showed a high correlation (r = 0.91) between heart rate measurements obtained from the Garmin Vivosmart and the Zephyr BioHarness, supporting its use for home-based heart rate monitoring. Participants will wear the device at home to facilitate real-time tracking of exercise intensity and physiological responses during the intervention. Advanced sleep tracking in compatible Garmin devices incorporates multiple factors to provide information on sleep patterns. In addition to basic information, such as sleep onset and wake-up time, researchers will be able to obtain data on periods of wakefulness and time spent in key sleep stages, including light, deep, and rapid eye movement (REM) sleep. |
Contacts
CONTACTHui-Hsun Chiang, Professor
Outcome results
None listed