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

Hancong Wu, Matthew Dyson, Kianoush Nazarpour

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.
Original languageEnglish
Article number763
Number of pages13
Issue number3
Early online date24 Jan 2021
Publication statusPublished - 1 Feb 2021

Keywords / Materials (for Non-textual outputs)

  • surface electromyogram
  • prosthesis control
  • wearable
  • low-cost


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