Lower Extremity Joint Angle Tracking with Wireless Ultrasonic Sensors during a Squat Exercise

Area of Science:

• Biomechanics
• Wearable Technology
• Sensor Networks

Background:

• Accurate kinematic analysis of lower extremity and trunk motion is crucial for evaluating exercise technique and guiding rehabilitation.
• Existing motion capture systems can be restrictive or complex, limiting their use in real-world settings.

Purpose of the Study:

• To develop and validate a novel, unrestrained wearable wireless ultrasonic sensor network for tracking lower extremity and trunk kinematics during squat exercises.
• To assess the accuracy and reliability of the ultrasonic system compared to a camera-based motion capture system.

Main Methods:

• A wireless ultrasonic sensor network with one mobile transmitter and multiple fixed receivers was employed.
• The system measured displacement, utilizing joint constraints and an inverse kinematic model (damped least-squares) to estimate joint angles.
• Performance was validated against a camera-based system with eight healthy subjects performing planar squats.

Main Results:

• The ultrasonic system achieved a root mean square error (RMSE) of 2.85° ± 0.57° for joint angle estimation compared to the reference system.
• High agreement was observed between the ultrasonic and camera-based systems, with Pearson's correlation coefficients (PCC) exceeding 0.99 for all joint angles.

Conclusions:

• The proposed wearable wireless ultrasonic sensor network provides accurate and reliable estimation of lower extremity and trunk kinematics.
• This system offers a promising, unrestrained solution for motion analysis in applications such as sports performance monitoring and physical rehabilitation.