AI-Adaptive AR Training for Balance and Falls Prevention in Older Adults
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age55-80
SponsorMcMaster University
About this trial
Falls are a common problem in adults within the age of 55-80 years and can lead to injury and loss of independence. This study is testing a new type of balance training using augmented reality (AR). In this intervention, participants will see virtual objects, such as obstacles, placed in their environment and will practice stepping over or moving around them. The system will adjust the difficulty based on each person's performance. Participants will complete training sessions over several weeks. We will measure changes in balance, walking ability, and confidence before and after the program. The goal is to see if this training can help improve balance and reduce the risk of falls in older adults.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Aged 55 - 80 years
Able to ambulate independently with or without an assistive device
Able to understand and follow instructions unimpeded by significant cognitive barriers (MoCA score must be 24/30 or higher)
Self-reported balance concerns or perceived risk of falls (e.g., reduced balance confidence)
Disqualifiers
Engaging in any additional balance or mobility training programs while participating in the study
Diagnosed neurological conditions that substantially impair balance or mobility (e.g., stroke, Parkinson's disease, Traumatic Brain Injury)
Medical conditions that contraindicate moderate physical activity
Vision impairment that cannot be corrected by glasses or lenses
Trial design
Design model
Single group
Treatments tested in this trial
AI-Enhanced Augmented Reality Balance and Mobility Training
DeviceParticipants will complete an 8-week AI-enhanced augmented reality (AR) balance and mobility training program, consisting of 3-5 sessions per week of approximately 30 minutes each. Using AR smart glasses connected to a dedicated smartphone, participants will perform standing- and walking-based tasks, including obstacle negotiation, path following, step targeting, turning, and directional changes. A machine learning model adapts task difficulty based on individual performance using a challenge-point framework targeting approximately 80% task success. Difficulty is iteratively increased or decreased based on performance, including adjustments to target speed and target size. Training may be completed at McMaster University or, following an initial supervised session and home safety assessment, at the participant's home.
Treatment groups
30 Participants
are divided into 1 treatment groupGroup A: Participants receive the 8-week AI-enhanced AR balance and mobility training, 3-5 sessions per week.Experimental treatment 1 intervention
Trial outcomes
Primary outcomes
1
Participant Retention Rate
Retention will be calculated as the percentage of enrolled participants who complete the post-intervention assessment (T2): number completing T2 divided by the number enrolled at baseline (T1), multiplied by 100.
Time frame
From baseline (T1) through post-intervention assessment (T2), approximately 8 weeks2
Adherence to the Augmented Reality Training Program
Adherence will be calculated for each participant as the percentage of prescribed AR training sessions completed during the 8-week intervention. Participants are prescribed 3-5 sessions per week, with each session lasting approximately 30 minutes.
Time frame
Throughout the 8-week intervention3
Weekly Augmented Reality Training Session Completion
Weekly training participation will be assessed based on the number of AR training sessions completed each week. Completion of 3-5 sessions per week will be used to characterize adherence to the intended training frequency.
Time frame
Weekly throughout the 8-week interventionSecondary outcomes
1
Change in Mini Balance Evaluation Systems Test (Mini-BESTest) Score
The Mini-BESTest assesses dynamic balance across anticipatory postural control, reactive postural responses, sensory orientation, and gait stability. Total scores range from 0 to 28, with higher scores indicating better balance performance.
Time frame
Baseline (T1) and immediately post-intervention (T2), approximately 8 weeks2
Change in Timed Up and Go (TUG) Performance
Functional mobility will be assessed using the Timed Up and Go test. Participants stand from a seated position, walk 3 metres, turn, return, and sit down. Performance is measured in seconds, with shorter completion times indicating better functional mobility.
Time frame
Baseline (T1) and immediately post-intervention (T2), approximately 8 weeks3
Change in Activities-specific Balance Confidence (ABC) Scale Score
The Activities-specific Balance Confidence (ABC) Scale will assess perceived confidence in maintaining balance during everyday activities. Scores are expressed as a percentage, with higher scores indicating greater balance confidence.
Time frame
Baseline (T1) and immediately post-intervention (T2), approximately 8 weeks4
Change in BTrackS Limits of Stability
Limits of Stability will assess the participant's ability to voluntarily control center of pressure within the base of support. Participants move a cursor representing center of pressure across a computer display while standing on the BTrackS force plate. Performance is quantified by the area covered in square centimetres (cm²).
Time frame
Baseline (T1) and immediately post-intervention (T2), approximately 8 weeksSponsors and contacts
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Source ClinicalTrials.gov
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