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Sensors 2016, 16(6), 766; doi:10.3390/s16060766

Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations

1
Mechanical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
2
Department of Biomedical Engineering, Catholic University of America, Washington, DC 20064, USA
3
Center for Applied Biomechanics and Rehabilitation Research, MedStar National Rehabilitation Hospital, Washington, DC 20010, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Yun Liu
Received: 7 April 2016 / Revised: 17 May 2016 / Accepted: 19 May 2016 / Published: 26 May 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [5097 KB, uploaded 26 May 2016]   |  

Abstract

Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices. View Full-Text
Keywords: wearable hand device; sensor locations; kinematic accuracy; 3D measurement; thumb-joint angle estimation wearable hand device; sensor locations; kinematic accuracy; 3D measurement; thumb-joint angle estimation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kim, D.H.; Lee, S.W.; Park, H.-S. Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations. Sensors 2016, 16, 766.

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