A Novel Physiologically-Inspired Method for Myoelectric Prosthesis Control Using Pattern Classification
Dosen S, Patel GK, Hahne JM, Farina D (2019)
Publication Type: Conference contribution
Publication year: 2019
Publisher: Springer International Publishing
Series: Biosystems and Biorobotics
City/Town: Cham
Book Volume: 21
Pages Range: 1017-1021
Conference Proceedings Title: Converging Clinical and Engineering Research on Neurorehabilitation III
Event location: Pisa
ISBN: 978-3-030-01845-0
DOI: 10.1007/978-3-030-01845-0_204
Abstract
The contemporary myoelectric prostheses are advanced mechatronic systems, but human-machine interfacing for robust control of these devices is still an open challenge. We present a novel method for the recognition of user intention based on pattern classification which is inspired by the natural coordination of multiple muscles during hand and wrist motions. The coordinated muscle activation produces a characteristic distribution of the amplitude features of the electromyography signals, and the novel method establishes the class boundaries to capture this natural distribution. The method has been tested in healthy subjects operating a prosthesis during a challenging functional task (bottle grasping, turning and releasing). The novel approach outperformed the commonly used benchmark (linear discriminant analysis), while using shorter training and fewer features. Further developments can, therefore, lead to a method that is suitable for practical implementation and allows robust and efficient control.
Authors with CRIS profile
Involved external institutions
Universitätsklinikum Göttingen
Germany (DE)
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) / German Aerospace Center
Germany (DE)
Germany (DE)
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) / German Aerospace Center
Germany (DE)
How to cite
APA:
Dosen, S., Patel, G.K., Hahne, J.M., & Farina, D. (2019). A Novel Physiologically-Inspired Method for Myoelectric Prosthesis Control Using Pattern Classification. In Lorenzo Masia, Silvestro Micera, Metin Akay, José L. Pons (Eds.), Converging Clinical and Engineering Research on Neurorehabilitation III (pp. 1017-1021). Pisa, IT: Cham: Springer International Publishing.
MLA:
Dosen, Strahinja, et al. "A Novel Physiologically-Inspired Method for Myoelectric Prosthesis Control Using Pattern Classification." Proceedings of the International Conference on NeuroRehabilitation, Pisa Ed. Lorenzo Masia, Silvestro Micera, Metin Akay, José L. Pons, Cham: Springer International Publishing, 2019. 1017-1021.
BibTeX: Download