Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
1
Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Weßling, Germany
2
Center of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, 33619 Bielefeld, Germany
3
Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, 79110 Freiburg, Germany
4
Machine Learning and Data Analytics Lab, Friedrich-Alexander University Erlangen-Nuernberg, 91058 Erlangen, Germany
*
Author to whom correspondence should be addressed.
Technologies 2018, 6(2), 38; https://doi.org/10.3390/technologies6020038
Received: 4 January 2018 / Revised: 12 March 2018 / Accepted: 21 March 2018 / Published: 23 March 2018
(This article belongs to the Special Issue Assistive Robotics)
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.
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Keywords:
tactile myography; tactile sensing; assistive robotics; human-machine interfaces; upper-limb prosthetics
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MDPI and ACS Style
Castellini, C.; Kõiva, R.; Pasluosta, C.; Viegas, C.; Eskofier, B.M. Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee. Technologies 2018, 6, 38. https://doi.org/10.3390/technologies6020038
AMA Style
Castellini C, Kõiva R, Pasluosta C, Viegas C, Eskofier BM. Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee. Technologies. 2018; 6(2):38. https://doi.org/10.3390/technologies6020038
Chicago/Turabian StyleCastellini, Claudio; Kõiva, Risto; Pasluosta, Cristian; Viegas, Carla; Eskofier, Björn M. 2018. "Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee" Technologies 6, no. 2: 38. https://doi.org/10.3390/technologies6020038
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