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

Yongbin Qi1, Cheong Boon Soh2, Erry Gunawan3

  • 1School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore. qiyo0001@e.ntu.edu.sg.

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Summary

A new wearable ultrasonic sensor system accurately tracks lower body and trunk movements during squats. This wireless technology offers a reliable, unrestrained method for analyzing joint kinematics in sports and rehabilitation.

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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.