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Arduino-based myoelectric control: Towards longitudinal study of prosthesis use

Lookup NU author(s): Dr Matthew Dyson, Professor Kianoush Nazarpour

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2021 by the authors. Licensee MDPI, Basel, Switzerland.Understanding how upper-limb prostheses are used in daily life helps to improve the design and robustness of prosthesis control algorithms and prosthetic components. However, only a very small fraction of published research includes prosthesis use in community settings. The cost, limited battery life, and poor generalisation may be the main reasons limiting the implementation of home-based applications. In this work, we introduce the design of a cost-effective Arduino-based myoelectric control system with wearable electromyogram (EMG) sensors. The design considerations focused on home studies, so the robustness, user-friendly control adjustments, and user supports were the main concerns. Three control algorithms, namely, direct control, abstract control, and linear discriminant analysis (LDA) classification, were implemented in the system. In this paper, we will share our design principles and report the robustness of the system in continuous operation in the laboratory. In addition, we will show a first real-time implementation of the abstract decoder for prosthesis control with an able-bodied participant.


Publication metadata

Author(s): Wu H, Dyson M, Nazarpour K

Publication type: Article

Publication status: Published

Journal: Sensors

Year: 2021

Volume: 21

Issue: 3

Pages: 1-13

Online publication date: 24/01/2021

Acceptance date: 20/01/2021

Date deposited: 08/04/2021

ISSN (electronic): 1424-8220

Publisher: MDPI AG

URL: https://doi.org/10.3390/s21030763

DOI: 10.3390/s21030763


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