Personalized Balance and Fall Risk Visualization with Kinect Two.

Area of Science:

• Biomechanics
• Rehabilitation Engineering
• Human-Computer Interaction

Background:

• Super-aging societies require efficient, cost-effective rehabilitation systems for the elderly and motor-impaired.
• Accurate human balance assessment is crucial for fall risk evaluation, relying on center of mass (CoM) displacement over the support polygon.
• Current methods use generic anthropometric tables or require specialized equipment like force platforms, limiting practical application.

Purpose of the Study:

• To develop a personalized, real-time system for evaluating balance and fall risk in individuals.
• To overcome limitations of generic anthropometric data and specialized measurement tools in fall risk assessment.
• To provide an efficient and accessible method for improving rehabilitation standards.

Main Methods:

• Utilized Kinect Two motion tracking for subject-specific body mass variations and movement analysis.
• Developed an adaptive support polygon extraction process for accurate foot tracking.
• Integrated these components to create a real-time balance and fall risk visualization system.

Main Results:

• Successfully verified the system using Kinect Two recordings.
• Demonstrated real-time evaluation of personalized balance and fall risk visualization.
• Eliminated the need for force platforms or other specialized equipment for fall risk assessment.

Conclusions:

• The developed system offers a personalized and practical approach to balance assessment and fall risk evaluation.
• This technology can significantly enhance rehabilitation efforts for the elderly and motor-impaired populations.
• The system provides an efficient, cost-effective, and accessible solution for daily life environments.