Disease Prevention
Conditions
Brief summary
A randomized controlled trial involving 30 older adults will compare the digitalized Brief-BESTest and the GDBA. Quantitative outcomes included perceived exertion, enjoyment, competence, pressure, and intention to continue use. Qualitative interviews explore user experience.
Interventions
The GDBA further enhances the digitalized Brief-BESTest experience by incorporating gamification elements tailored to older adults, including points, avatars, real-time performance graphs, and leaderboards. The system provides automated feedback and maintains engagement through periodic avatar demonstrations when user inactivity is detected. Upon meeting task initiation criteria, a countdown triggers data capture. The interface is designed for accessibility, featuring a high-contrast color scheme (black background with orange/green highlights), voice prompts, and intuitive controls. Upon completion, users receive a comprehensive report including total score, task-level feedback and training recommendations. A leaderboard feature promotes continued engagement, with gamified training modules under development. At the end of the assessment, the system displays a summary including total balance score, task-specific feedback, a fall risk rating, and personalized training suggestions. Users
The digitalized Brief-BESTest was designed to digitize and automate the Brief-BESTest. While the traditional clinician-administered Brief-BESTest relies on subjective scoring, the digitalized Brief-BESTest enables self-guided assessments with automated, objective scoring-improving accessibility in community and home settings. The system employs OpenPose to capture skeletal data via a standard 2D camera, tracking 17 anatomical landmarks (e.g., nose, neck, shoulders, hips, knees). Ten joint angles relevant to static and dynamic postural tasks (e.g., standing, sitting, single-leg stance, and simulated falls) are computed. The torso is defined as a vector from the neck to the midpoint between the hips, serving as a reference for postural alignment. To convert pixel-based coordinates into metric units, the system uses the user's self-reported height with adjustments based on ISO anthropometric standards (correction factors: 10.77 cm for males, 10.06 cm for females) to approximate true body
Sponsors
Study design
Eligibility
Inclusion criteria
* aged 60 or older, living independently, able to walk with or without an assistive device (without external help), willing and able to provide informed consent.
Exclusion criteria
* conditions that impede walking (e.g., hip fractures, lower limb amputations, hemiparesis), medications causing dizziness or affecting balance (e.g., psychotropic drugs), self-reported cardiovascular, pulmonary, neurological, musculoskeletal, or mental disorders, severe fatigue or pain, severe uncorrected vision or hearing impairments that may affect their ability to interact with the digital system
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Balance Performance: | Through intervention completion, an average of 10 mins | Balance ability was assessed using the digitalized Brief-BESTest |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Fatigue level | Through intervention completion, an average of 10 mins | Motivational engagement was evaluated using the Intrinsic Motivation Inventory (IMI) |
Countries
China