Development and Assessment of Artificial Intelligence-Empowered Gait Monitoring System Using Single Inertial Sensor

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Wearable Sensors

Background:

• Gait instability is a significant concern in healthcare, linked to balance disorders and physical impairment.
• Existing wearable gait monitoring systems often require extensive effort for gait metric extraction.
• There is a need for efficient, cost-effective gait analysis solutions.

Purpose of the Study:

• To design an artificial intelligence (AI)-empowered and economically viable gait monitoring system.
• To develop intelligent shoes with inertial sensors and a smartphone application for gait analysis.
• To accurately measure gait cycle, stand phase time, swing phase time, stride length, and foot clearance.

Main Methods:

• Development of intelligent shoes equipped with a single inertial sensor.
• Integration with a smartphone application for data processing and analysis.
• Validation of system accuracy using a Vicon motion capture system with 30 participants.

Main Results:

• The AI-empowered system demonstrated high accuracy in assessing gait metrics.
• Achieved 96.17% accuracy for stride length measurement.
• Achieved 92.07% accuracy for foot clearance measurement.

Conclusions:

• The developed AI-empowered gait monitoring system offers a promising, cost-effective solution for gait analysis.
• The system accurately quantifies key gait parameters, supporting medical and healthcare applications.
• This technology has the potential to significantly improve gait monitoring and analysis in clinical settings.