Development of a Low-Cost Wearable Data Glove for Capturing Finger Joint Angles

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ID: 272229
2021
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Abstract
Capturing finger joint angle information has important applications in human–computer interaction and hand function evaluation. In this paper, a novel wearable data glove is proposed for capturing finger joint angles. A sensing unit based on a grating strip and an optical detector is specially designed for finger joint angle measurement. To measure the angles of finger joints, 14 sensing units are arranged on the back of the glove. There is a sensing unit on the back of each of the middle phalange, proximal phalange, and metacarpal of each finger, except for the thumb. For the thumb, two sensing units are distributed on the back of the proximal phalange and metacarpal, respectively. Sensing unit response tests and calibration experiments are conducted to evaluate the feasibility of using the designed sensing unit for finger joint measurement. Experimental results of calibration show that the comprehensive precision of measuring the joint angle of a wooden finger model is 1.67%. Grasping tests and static digital gesture recognition experiments are conducted to evaluate the performance of the designed glove. We achieve a recognition accuracy of 99% by using the designed glove and a generalized regression neural network (GRNN). These preliminary experimental results indicate that the designed data glove is effective in capturing finger joint angles.
Reference Key
wu2021micromachinesdevelopment Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Changcheng Wu;Keer Wang;Qingqing Cao;Fei Fei;Dehua Yang;Xiong Lu;Baoguo Xu;Hong Zeng;Aiguo Song;Wu, Changcheng;Wang, Keer;Cao, Qingqing;Fei, Fei;Yang, Dehua;Lu, Xiong;Xu, Baoguo;Zeng, Hong;Song, Aiguo;
Journal micromachines
Year 2021
DOI
10.3390/mi12070771
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