Data Glove System Embedded With Inertial Measurement Units for Hand Function Evaluation in Stroke Patients
Summary
This novel data glove system uses inertial sensors to assess stroke patient hand function, aiding physicians in treatment adjustments. The system achieved a 70.22% accuracy rate in evaluating hand function for rehabilitation.
Area of Science:
- Biomedical Engineering
- Rehabilitation Technology
- Neuroscience
Background:
- Stroke significantly impairs hand function, necessitating accurate assessment tools for effective rehabilitation.
- Current methods for evaluating hand function in stroke patients can be subjective and time-consuming.
- Brunnstrom stages (BSs) are used to classify motor recovery but require objective quantification.
Purpose of the Study:
- To propose and evaluate a modular data glove system with six-axis inertial measurement unit (IMU) sensors for objective hand function assessment in stroke patients.
- To investigate the system's ability to provide quantitative data for insights into rehabilitation treatments.
- To assess the system's effectiveness in aiding physicians in determining Brunnstrom stages (BSs).
Main Methods:
- A data glove system integrated with six-axis IMU sensors was developed.
- A quaternion algorithm was used to calculate hand accelerations, angular velocities, and joint angles.
- Clinical experiments involved 15 healthy subjects and 15 stroke patients (BSs 4-6) performing grip, thumb, and card turning tasks.
- Features extracted included average rotation speed, movement completion time variation, and movement quality, visualized in 2-D and 3-D scatter plots.
Main Results:
- The system successfully captured hand function data, including accelerations, angular velocities, and joint angles.
- Extracted features (average rotation speed, movement completion time variation, movement quality) were used to create diagnostic scatter plots.
- The proposed system demonstrated an average hit rate of 70.22% in classifying hand function and aiding BS determination.
- Scatter plots provided valuable reference information for physicians regarding stroke patient hand function.
Conclusions:
- The data glove system offers an objective and effective method for evaluating hand function in stroke patients.
- The system aids physicians by reducing workload and providing detailed insights for adjusting rehabilitation strategies.
- This technology has the potential to enhance the precision and efficiency of stroke rehabilitation assessment.
