Measuring clinically relevant knee motion with a self-calibrated wearable sensor.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Wearable Sensors

Background:

• Low-cost sensors offer potential for continuous patient monitoring during rehabilitation.
• Current low-cost sensors lack the necessary fidelity and calibration methods for clinical research.

Purpose of the Study:

• To validate a low-cost wearable sensor for accurate measurement of peak knee extension.
• To assess a sensor requiring no additional equipment for calibration.

Main Methods:

• A 9-axis motion sensor quantified sagittal plane knee motion.
• Sensor data was directly compared to gold-standard motion capture.
• A simple calibration process correlated magnet field strength with knee angle.

Main Results:

• Peak knee extension during seated exercises was accurate within 5 degrees (RMSE: 2.6°).
• Knee flexion during gait showed strong correlation (r=0.84–0.99) but had peak errors of 10 degrees.
• The sensor (≈$35) demonstrated accurate knee extension angle measurement post-calibration.

Conclusions:

• This low-cost sensor paradigm is a feasible tool for monitoring rehabilitation progress.
• The sensor provides accurate knee extension measurements with a simple, equipment-free calibration.
• Soft-tissue artifact may limit accuracy during dynamic movements.