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Ahkami B, Ahmed K, Thesleff A, Hargrove L, Ortiz-Catalan M. Electromyography-Based Control of Lower Limb Prostheses: A Systematic Review. IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS 2023; 5:547-562. [PMID: 37655190 PMCID: PMC10470657 DOI: 10.1109/tmrb.2023.3282325] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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.
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Affiliation(s)
- Bahareh Ahkami
- Center for Bionics and Pain Research, 43130 Mölndal, Sweden, and also with the Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden
| | - Kirstin Ahmed
- Center for Bionics and Pain Research, 43130 Mölndal, Sweden, and also with the Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden
| | - Alexander Thesleff
- Center for Bionics and Pain Research, 43130 Mölndal, Sweden, also with the Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden, and also with Integrum AB, 43153 Molndal, Sweden
| | - Levi Hargrove
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL 60611 USA, and also with the Regenstein Foundation Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL 60611 USA
| | - Max Ortiz-Catalan
- Center for Bionics and Pain Research, 43130 Mölndal, Sweden, also with the Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden, also with the Operational Area 3, Sahlgrenska University Hospital, 41345 Gothenburg, Sweden, and also with Bionics Institute, Melbourne, VIC 3002, Australia
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Wei C, Wang H, Hu F, Zhou B, Feng N, Lu Y, Tang H, Jia X. Single-channel surface electromyography signal classification with variational mode decomposition and entropy feature for lower limb movements recognition. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2022.103487] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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