Sharif-Human movement instrumentation system (SHARIF-HMIS): Development and validation

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Human Motion Analysis

Background:

• Wearable systems are increasingly vital in biomedical engineering and clinical settings.
• Microelectromechanical systems (MEMS) show significant potential for biomedical applications.
• Existing systems often require controlled laboratory environments, limiting real-world utility.

Purpose of the Study:

• To investigate the Sharif-Human Movement Instrumentation System (SHARIF-HMIS) for outdoor human motion analysis.
• To evaluate a novel data-fusion algorithm employing an adaptive Kalman filter.
• To assess the system's utility in non-laboratory settings.

Main Methods:

• Developed SHARIF-HMIS integrating inertial measurement units (IMUs) into stretchable clothing with a data logger.
• Implemented an adaptive Kalman filter for sensor data fusion (gyroscope, accelerometer, magnetometer) to estimate total-body orientation.
• Acquired kinematic data from eighteen IMUs during human motion tasks.
• Validated SHARIF-HMIS against a VICON motion-capture system.

Main Results:

• SHARIF-HMIS demonstrated high correlation (>0.9) with VICON system data for shoulder motions.
• Achieved sensor output accuracy of <0.55°, 1.5°, and 3.5° for roll, pitch, and yaw, respectively.
• The system is lightweight, portable, and provides data for nearly 10 hours.

Conclusions:

• SHARIF-HMIS successfully captures kinematic data for human movements outside laboratory settings.
• The adaptive Kalman filter effectively handles sensor noise and magnetic disturbances.
• The system holds significant promise for sporting, biomedical, and healthcare applications.