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Simultaneous assessment and training of an upper-limb amputee using incremental machine-learning-based myocontrol: a single-case experimental design

Nowak, Markus and Bongers, Raoul M. and van der Sluis, Corry K. and Castellini, Claudio and Albu-Schäffer, Alin (2023) Simultaneous assessment and training of an upper-limb amputee using incremental machine-learning-based myocontrol: a single-case experimental design. Journal of NeuroEngineering and Rehabilitation, 20 (39). Springer Nature. doi: 10.1186/s12984-023-01171-2. ISSN 1743-0003.

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Official URL: https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-023-01171-2


Background Machine-learning-based myocontrol of prosthetic devices suffers from a high rate of abandonment due to dissatisfaction with the training procedure and with the reliability of day-to-day control. Incremental myocontrol is a promising approach as it allows on-demand updating of the system, thus enforcing continuous interaction with the user. Nevertheless, a long-term study assessing the efficacy of incremental myocontrol is still missing, partially due to the lack of an adequate tool to do so. In this work we close this gap and report about a person with upper-limb absence who learned to control a dexterous hand prosthesis using incremental myocontrol through a novel functional assessment protocol called SATMC (Simultaneous Assessment and Training of Myoelectric Control). Methods The participant was fitted with a custom-made prosthetic setup with a controller based on Ridge Regression with Random Fourier Features (RR-RFF), a non-linear, incremental machine learning method, used to build and progressively update the myocontrol system. During a 13-month user study, the participant performed increasingly complex daily-living tasks, requiring fine bimanual coordination and manipulation with a multi-fingered hand prosthesis, in a realistic laboratory setup. The SATMC was used both to compose the tasks and continually assess the participant's progress. Patient satisfaction was measured using Visual Analog Scales. Results Over the course of the study, the participant progressively improved his performance both objectively, e.g., the time required to complete each task became shorter, and subjectively, meaning that his satisfaction improved. The SATMC actively supported the improvement of the participant by progressively increasing the difficulty of the tasks in a structured way. In combination with the incremental RR-RFF allowing for small adjustments when required, the participant was capable of reliably using four actions of the prosthetic hand to perform all required tasks at the end of the study. Conclusions Incremental myocontrol enabled an upper-limb amputee to reliably control a dexterous hand prosthesis while providing a subjectively satisfactory experience. The SATMC can be an effective tool to this aim.

Item URL in elib:https://elib.dlr.de/194687/
Document Type:Article
Title:Simultaneous assessment and training of an upper-limb amputee using incremental machine-learning-based myocontrol: a single-case experimental design
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Nowak, MarkusUNSPECIFIEDhttps://orcid.org/0000-0002-0840-5155UNSPECIFIED
Bongers, Raoul M.University of Groningen, The NetherlandsUNSPECIFIEDUNSPECIFIED
van der Sluis, Corry K.University of Groningen, The NetherlandsUNSPECIFIEDUNSPECIFIED
Castellini, ClaudioUNSPECIFIEDhttps://orcid.org/0000-0002-7346-2180UNSPECIFIED
Albu-Schäffer, AlinUNSPECIFIEDhttps://orcid.org/0000-0001-5343-9074142115936
Date:7 April 2023
Journal or Publication Title:Journal of NeuroEngineering and Rehabilitation
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Publisher:Springer Nature
Keywords:Hand prosthesis, Machine-learning control, Myocontrol, Training, Single-case experimental design
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Terrestrial Assistance Robotics, R - Intelligent Mobility (RM) [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Institute of Robotics and Mechatronics (since 2013) > Cognitive Robotics
Deposited By: Nowak, Markus
Deposited On:02 May 2023 16:39
Last Modified:11 Sep 2023 13:25

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