Evaluating a Kinematic Data Glove with Pressure Sensors to Automatically Differentiate Free Motion from Product Manipulation
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comunitat-uji-handle3:10234/8617
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INVESTIGACIONMetadata
Title
Evaluating a Kinematic Data Glove with Pressure Sensors to Automatically Differentiate Free Motion from Product ManipulationDate
2023-08-01Publisher
MDPIISSN
2076-3417Bibliographic citation
Roda-Sales, A.; Sancho-Bru, J.L.; Vergara, M. Evaluating a Kinematic Data Glove with Pressure Sensors to Automatically Differentiate Free Motion from Product Manipulation. Appl. Sci. 2023, 13, 8765. https://doi.org/10.3390/app13158765Type
info:eu-repo/semantics/articlePublisher version
https://www.mdpi.com/2076-3417/13/15/8765Version
info:eu-repo/semantics/publishedVersionSubject
Abstract
When studying hand kinematics, it is key to differentiate between free motion and manipulation. This differentiation can be achieved using pressure sensors or through visual analysis in the absence of sensors. Certain ... [+]
When studying hand kinematics, it is key to differentiate between free motion and manipulation. This differentiation can be achieved using pressure sensors or through visual analysis in the absence of sensors. Certain data gloves, such as the CyberGlove II, allow recording hand kinematics with good accuracy when properly calibrated. Other gloves, such as the Virtual Motion Glove 30 (VMG30), are also equipped with pressure sensors to detect object contact. The aim of this study is to perform a technical validation to evaluate the feasibility of using virtual reality gloves with pressure sensors such as the VMG30 for hand kinematics characterization during product manipulation, testing its accuracy for motion recording when compared with CyberGlove as well as its ability to differentiate between free motion and manipulation using its pressure sensors in comparison to visual analysis. Firstly, both data gloves were calibrated using a specific protocol developed by the research group. Then, the active ranges of motion of 16 hand joints angles were recorded in three participants using both gloves and compared using repeated measures ANOVAs. The detection capability of pressure sensors was compared to visual analysis in two participants while performing six tasks involving product manipulation. The results revealed that kinematic data recordings from the VMG30 were less accurate than those from the CyberGlove. Furthermore, the pressure sensors did not provide additional precision with respect to the visual analysis technique. In fact, several pressure sensors were rarely activated, and the distribution of pressure sensors within the glove was questioned. Current available gloves such as the VMG30 would require design improvements to fit the requirements for kinematics characterization during product manipulation. The pressure sensors should have higher sensitivity, the pressure sensor’s location should comprise the palm, glove fit should be improved, and its overall stiffness should be reduced. [-]
Is part of
Applied Sciences, 2023, vol. 13, no 15Related data
https://doi.org/10.5281/zenodo.8193094Funder Name
Agencia Financiadora: Ministerio de Ciencia, Innovación y Universidades | Generalitat Valenciana
Funder ID
http://dx.doi.org/10.13039/501100011033
Project code
MICIU/ICTI2017-2020/PGC2018-095606-B-C21 | CIGE/2021/024
Project title or grant
Caracterización de movimientos y esfuerzos musculares de la mano sana orientada a la evaluación funcional y al diseño y adaptación de productos para manipulación
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info:eu-repo/semantics/openAccess
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