Electromyography-Based Control of Lower Limb Prostheses: A Systematic Review

Bahareh Ahkami, Kirstin Ahmed, Alexander Thesleff, Levi Hargrove, Max Ortiz-Catalan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Most amputations occur in lower limbs and despite improvements in prosthetic technology, no commercially available prosthetic leg uses electromyography (EMG) information as an input for control. Efforts to integrate EMG signals as part of the control strategy have increased in the last decade. In this systematic review, we summarize the research in the field of lower limb prosthetic control using EMG. Four different online databases were searched until June 2022: Web of Science, Scopus, PubMed, and Science Direct. We included articles that reported systems for controlling a prosthetic leg (with an ankle and/or knee actuator) by decoding gait intent using EMG signals alone or in combination with other sensors. A total of 1,331 papers were initially assessed and 121 were finally included in this systematic review. The literature showed that despite the burgeoning interest in research, controlling a leg prosthesis using EMG signals remains challenging. Specifically, regarding EMG signal quality and stability, electrode placement, prosthetic hardware, and control algorithms, all of which need to be more robust for everyday use. In the studies that were investigated, large variations were found between the control methodologies, type of research participant, recording protocols, assessments, and prosthetic hardware.

Original languageEnglish (US)
Pages (from-to)547-562
Number of pages16
JournalIEEE Transactions on Medical Robotics and Bionics
Volume5
Issue number3
DOIs
StatePublished - Aug 1 2023

Keywords

  • Electromyography (EMG)
  • control algorithms
  • control architecture
  • lower limb amputation
  • movement intention recognition
  • pattern recognition

ASJC Scopus subject areas

  • Control and Optimization
  • Artificial Intelligence
  • Human-Computer Interaction
  • Biomedical Engineering
  • Computer Science Applications

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