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

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 chall...

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Autores principales: Kim, Dong Hyun, Lee, Sang Wook, Park, Hyung-Soon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934192/
https://www.ncbi.nlm.nih.gov/pubmed/27240364
http://dx.doi.org/10.3390/s16060766
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author Kim, Dong Hyun
Lee, Sang Wook
Park, Hyung-Soon
author_facet Kim, Dong Hyun
Lee, Sang Wook
Park, Hyung-Soon
author_sort Kim, Dong Hyun
collection PubMed
description 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.
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spelling pubmed-49341922016-07-06 Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations Kim, Dong Hyun Lee, Sang Wook Park, Hyung-Soon Sensors (Basel) Article 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. MDPI 2016-05-26 /pmc/articles/PMC4934192/ /pubmed/27240364 http://dx.doi.org/10.3390/s16060766 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Dong Hyun
Lee, Sang Wook
Park, Hyung-Soon
Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations
title Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations
title_full Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations
title_fullStr Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations
title_full_unstemmed Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations
title_short Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations
title_sort improving kinematic accuracy of soft wearable data gloves by optimizing sensor locations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934192/
https://www.ncbi.nlm.nih.gov/pubmed/27240364
http://dx.doi.org/10.3390/s16060766
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