Optimised EMG pipeline for gesture classification

Jarlath Warner*, Richard Gault, John McAllister

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
137 Downloads (Pure)

Abstract

In the expanding field of robotic prosthetics, surface electromyography (sEMG) signals can be decoded to seamlessly control a robotic prosthesis to perform the desired gesture. It is essential to create a pipeline, which can acquire, process, and accurately classify sEMG signals in order to replicate the desired hand gesture in near real-time and in a reliable manner. In this study, an optimised pipeline is proposed. This pipeline encompasses the main stages of sEMG signal processing and hand gesture classification and implements a sliding window approach, which is the main focus of the optimisation. In this study, a range of different parameters and modelling approaches are evaluated. The main contributions of this work are a robust and extensive analysis of sliding window parameter selection and an optimised pipeline that could be implemented in practice with minimal overheads. The optimum pipeline is efficient and achieves accurate prediction of hand gestures with an uninterrupted processing pipeline.
Original languageEnglish
Title of host publication44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2022: Proceedings
Pages3628-3631
Number of pages4
DOIs
Publication statusPublished - 08 Sept 2022
Event44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2022: Biomedical Engineering transforming the provision of healthcare: promoting wellness through personalized & predictable provision at the point of care - Scottish Events Campus (SEC), Glasgow, United Kingdom
Duration: 11 Jul 202215 Jul 2022
Conference number: 44
https://embc.embs.org/2022/

Conference

Conference44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2022
Abbreviated titleEMBC
Country/TerritoryUnited Kingdom
CityGlasgow
Period11/07/202215/07/2022
Internet address

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • EMG
  • EMG, LMA, gestural control
  • Machine learning, Decision tree, Concept drift, Ensemble learning, Classification, Random forest
  • Machine Learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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