NCT07088848

Gamified Digital Balance Assessment

Evaluating the Effectiveness of a Gamification in Balance Assessment Tools

• Status: Active Not Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 30 (estimated)
• Sponsor: Shanghai Jiao Tong University School of Medicine · Academic / Other
• Sex: All
• Age: 60 Years
• Healthy volunteers: Accepted

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.

Conditions

• Disease Prevention

Interventions

Type	Name	Description
DEVICE	Gamified Digital Balance Assessment	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
DEVICE	Digitalized Brief-BESTest design	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

Timeline

• Start date: 2025-04-20
• Primary completion: 2025-08-10
• Completion: 2025-12-20
• First posted: 2025-07-28
• Last updated: 2025-07-28

Locations

1 site across 1 country: China