Development of a Wearable Glove System with Multiple Sensors for Hand Kinematics Assessment

In traditional hand function assessment, patients and physicians always need to accomplish complex activities and rating tasks. This paper proposes a novel wearable glove system for hand function assessment. A sensing system consisting of 12 nine-axis inertial and magnetic unit (IMMU) sensors is used to obtain the acceleration, angular velocity, and geomagnetic orientation of human hand movements. A complementary filter algorithm is applied to calculate the angles of joints after sensor calibration. A virtual hand model is also developed to map with the glove system in the Unity platform. The experimental results show that this glove system can capture and reproduce human hand motions with high accuracy. This smart glove system is expected to reduce the complexity and time consumption of hand kinematics assessment.

Automated summary

This study introduces a novel wearable glove system for hand function assessment, which uses sensors to capture hand movements and a complementary filter algorithm to calculate joint angles, while also developing a virtual hand model. Experimental results demonstrate that this smart glove system can accurately capture and reproduce human hand motions, potentially reducing the complexity and time consumption of hand kinematics assessment.