Wearable Device Development for Precise Hand Function and Fatigue Assessment Using IMU Sensors

Accurate and quantitative assessments of hand function are essential for developing effective rehabilitation training programs, as they can prevent secondary injuries resulting from overtraining or incorrect movements. In this study, a wearable device utilizing four six-axis inertial sensors (IMUs) was developed to provide precise kinematic parameters of finger movements for hand function assessment. The accuracy of the accelerations, angular velocities, and joint angles measured by the data glove was thoroughly validated. Grasping and finger-tapping experiments were conducted, followed by processing and analysis of data such as angular velocity and joint angles. The objective was to assess the range of motion of the index finger joints and evaluate hand fatigue. The experimental results demonstrated that the wearable device developed in this study accurately captures hand kinematics. The grasping experiment effectively visualized the range of motion of the finger joints, while the finger-tapping experiment revealed a decline in the frequency and amplitude of angular velocity over time, indicating the presence of finger fatigue. Consequently, the wearable device proposed in this study proves to be a reliable and effective tool for personalized hand function assessment before rehabilitation.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1109/cisp-bmei64163.2024.10906099
Citations
1
Primary Topic
Ergonomics and Musculoskeletal Disorders
Type
article
Field-Weighted Citation Impact
0.64
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Wearable Device Development for Precise Hand Function and Fatigue Assessment Using IMU Sensors

Xu Zhou, Yuqi Gao, Zheng-Wei Zhou, Tao Liu et al.
1 citations
Ergonomics and Musculoskeletal Disorders
0.64
article

Wearable Device Development for Precise Hand Function and Fatigue Assessment Using IMU Sensors

Xu Zhou, Yuqi Gao, Zheng-Wei Zhou, Tao Liu, Chao Yu
article en
1 citations

Abstract

Accurate and quantitative assessments of hand function are essential for developing effective rehabilitation training programs, as they can prevent secondary injuries resulting from overtraining or incorrect movements. In this study, a wearable device utilizing four six-axis inertial sensors (IMUs) was developed to provide precise kinematic parameters of finger movements for hand function assessment. The accuracy of the accelerations, angular velocities, and joint angles measured by the data glove was thoroughly validated. Grasping and finger-tapping experiments were conducted, followed by processing and analysis of data such as angular velocity and joint angles. The objective was to assess the range of motion of the index finger joints and evaluate hand fatigue. The experimental results demonstrated that the wearable device developed in this study accurately captures hand kinematics. The grasping experiment effectively visualized the range of motion of the finger joints, while the finger-tapping experiment revealed a decline in the frequency and amplitude of angular velocity over time, indicating the presence of finger fatigue. Consequently, the wearable device proposed in this study proves to be a reliable and effective tool for personalized hand function assessment before rehabilitation.

University of Science and Technology of China (CN), Anhui University (CN), Chinese Academy of Sciences (CN), Hefei Institutes of Physical Science (CN)
Openalex Percentile: Top 23%
Ergonomics and Musculoskeletal Disorders
0.64
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