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IoT Technologies for HealthCare. 9th EAI International Conference, HealthyIoT 2022, Braga, Portugal, November 16-18, 2022, Proceedings

Research Article

A Low-Cost Open-Source Bionic Hand Controller: Preliminary Results and Perspectives

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-28663-6_3,
        author={Sandra Rodrigues and Milton P. Macedo},
        title={A Low-Cost Open-Source Bionic Hand Controller: Preliminary Results and Perspectives},
        proceedings={IoT Technologies for HealthCare. 9th EAI International Conference, HealthyIoT 2022, Braga, Portugal, November 16-18, 2022, Proceedings},
        proceedings_a={HEALTHYIOT},
        year={2023},
        month={3},
        keywords={Electromyography (EMG) Mechanomyography (MMG) Bionic hand Biomedical sensors Feature extraction},
        doi={10.1007/978-3-031-28663-6_3}
    }
    
  • Sandra Rodrigues
    Milton P. Macedo
    Year: 2023
    A Low-Cost Open-Source Bionic Hand Controller: Preliminary Results and Perspectives
    HEALTHYIOT
    Springer
    DOI: 10.1007/978-3-031-28663-6_3
Sandra Rodrigues1, Milton P. Macedo1,*
  • 1: Instituto Politécnico de Coimbra, ISEC, DFM, Rua Pedro Nunes, Quinta da Nora
*Contact email: mpmacedo@isec.pt

Abstract

This paper presents the current state of an ongoing project for the implementation of a low-cost bionic hand controller. Research had been conducted to evaluate the possibility of using MechanoMyoGraphic signals (MMG) as an alternative to ElectroMyoGraphic signals (EMG) that are usually acquired. Moreover the application of two novel and low-cost electrodes, one built from a conductive leather material, and another based on desktop 3D printing using conductive PLA (PolyLactic Acid), as an alternative to traditional pre-gelled Ag/AgCl electrodes was also evaluated. In addition to the search for the optimization of the quality of acquired signals, a solution for the control of the bionic hand had also been implemented using a very low-cost microcontroller (Arduino UNO). Results will be briefly presented from these works already carried out. A particular emphasis should be given to the success rate attained of 100% on detecting three out of four gestures selected, when using this very low-cost hardware platform. However false activations were a weakness of this solution. In order to optimize bionic hand control, the simultaneous application of three types of sensors (EMG, force and accelerometer) is ongoing. A description of this implementation as well as a presentation of its preliminary results will also be made.

Keywords
Electromyography (EMG) Mechanomyography (MMG) Bionic hand Biomedical sensors Feature extraction
Published
2023-03-16
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-28663-6_3
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