Capturing Upper Body Kinematics and Localization with Low-Cost Sensors for Rehabilitation Applications

Area of Science:

• Rehabilitation Engineering
• Biomedical Signal Processing
• Wearable Technology

Background:

• Quantitative measurements are crucial for upper extremity rehabilitation, especially in telemedicine.
• Understanding patient movement and location provides context for therapy needs.

Purpose of the Study:

• To develop and evaluate algorithms for Bluetooth-based localization and IMU-based upper body kinematics.
• To assess the accuracy of these systems for remote patient monitoring in rehabilitation.

Main Methods:

• A new Bluetooth received signal strength (RSS) algorithm was developed for localization.
• Upper body kinematics were inferred using three inertial measurement unit (IMU) sensors (wrists and pelvis).
• Experimental evaluations were conducted for both localization and kinematics reconstruction.

Main Results:

• Bluetooth localization achieved a mean square error of 1.78 m.
• Kinematics reconstruction showed lower errors with specific sensor placement and calibration.
• Mean angular error for upper body segments was ~21 degrees; elbow/shoulder angles had <4 degrees error.

Conclusions:

• The developed algorithms show promise for quantitative, remote upper extremity rehabilitation monitoring.
• Accurate localization and kinematics tracking can inform targeted therapeutic interventions.
• This technology supports enhanced telemedicine capabilities for physical therapy.