Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee

Human-machine interfaces to control prosthetic devices still suffer from scarce dexterity and low reliability; for this reason, the community of assistive robotics is exploring novel solutions to the problem of myocontrol. In this work, we present experimental results pointing in the direction that...

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Main Authors: Claudio Castellini, Risto Kõiva, Cristian Pasluosta, Carla Viegas, Björn M. Eskofier
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Technologies
Subjects:
Online Access:http://www.mdpi.com/2227-7080/6/2/38
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spelling doaj-27714285673d4e529a4c44487b09ec7c2020-11-25T02:31:36ZengMDPI AGTechnologies2227-70802018-03-01623810.3390/technologies6020038technologies6020038Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb AmputeeClaudio Castellini0Risto Kõiva1Cristian Pasluosta2Carla Viegas3Björn M. Eskofier4Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Weßling, GermanyCenter of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, 33619 Bielefeld, GermanyLaboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, 79110 Freiburg, GermanyInstitute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Weßling, GermanyMachine Learning and Data Analytics Lab, Friedrich-Alexander University Erlangen-Nuernberg, 91058 Erlangen, GermanyHuman-machine interfaces to control prosthetic devices still suffer from scarce dexterity and low reliability; for this reason, the community of assistive robotics is exploring novel solutions to the problem of myocontrol. In this work, we present experimental results pointing in the direction that one such method, namely Tactile Myography (TMG), can improve the situation. In particular, we use a shape-conformable high-resolution tactile bracelet wrapped around the forearm/residual limb to discriminate several wrist and finger activations performed by able-bodied subjects and a trans-radial amputee. Several combinations of features/classifiers were tested to discriminate among the activations. The balanced accuracy obtained by the best classifier/feature combination was on average 89.15% (able-bodied subjects) and 88.72% (amputated subject); when considering wrist activations only, the results were on average 98.44% for the able-bodied subjects and 98.72% for the amputee. The results obtained from the amputee were comparable to those obtained by the able-bodied subjects. This suggests that TMG is a viable technique for myoprosthetic control, either as a replacement of or as a companion to traditional surface electromyography.http://www.mdpi.com/2227-7080/6/2/38tactile myographytactile sensingassistive roboticshuman-machine interfacesupper-limb prosthetics
collection DOAJ
language English
format Article
sources DOAJ
author Claudio Castellini
Risto Kõiva
Cristian Pasluosta
Carla Viegas
Björn M. Eskofier
spellingShingle Claudio Castellini
Risto Kõiva
Cristian Pasluosta
Carla Viegas
Björn M. Eskofier
Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
Technologies
tactile myography
tactile sensing
assistive robotics
human-machine interfaces
upper-limb prosthetics
author_facet Claudio Castellini
Risto Kõiva
Cristian Pasluosta
Carla Viegas
Björn M. Eskofier
author_sort Claudio Castellini
title Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
title_short Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
title_full Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
title_fullStr Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
title_full_unstemmed Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
title_sort tactile myography: an off-line assessment of able-bodied subjects and one upper-limb amputee
publisher MDPI AG
series Technologies
issn 2227-7080
publishDate 2018-03-01
description Human-machine interfaces to control prosthetic devices still suffer from scarce dexterity and low reliability; for this reason, the community of assistive robotics is exploring novel solutions to the problem of myocontrol. In this work, we present experimental results pointing in the direction that one such method, namely Tactile Myography (TMG), can improve the situation. In particular, we use a shape-conformable high-resolution tactile bracelet wrapped around the forearm/residual limb to discriminate several wrist and finger activations performed by able-bodied subjects and a trans-radial amputee. Several combinations of features/classifiers were tested to discriminate among the activations. The balanced accuracy obtained by the best classifier/feature combination was on average 89.15% (able-bodied subjects) and 88.72% (amputated subject); when considering wrist activations only, the results were on average 98.44% for the able-bodied subjects and 98.72% for the amputee. The results obtained from the amputee were comparable to those obtained by the able-bodied subjects. This suggests that TMG is a viable technique for myoprosthetic control, either as a replacement of or as a companion to traditional surface electromyography.
topic tactile myography
tactile sensing
assistive robotics
human-machine interfaces
upper-limb prosthetics
url http://www.mdpi.com/2227-7080/6/2/38
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