Comparison of Intramuscular and Surface Electromyography Recordings towards the Control of Wearable Robots for Incomplete Spinal Cord Injury Rehabilitation
Paper in proceeding, 2020

Spinal Cord Injury (SCI) affects thousands of people worldwide every year. SCI patients have disrupted muscle recruitment and are more predisposed to other complications. To recover or enhance lower limbs functions, conventional rehabilitation programs are typically used. More recently, conventional programs have been combined with robot-assisted training. Electromyography (EMG) activity is generally used to record the electrical activity of the muscles, which in turn can be used to control robotic assistive devices as orthoses, prostheses and exoskeletons. In this sense, surface EMG can be used as input to myoelectric control but presents some limitations such as myoelectric crosstalk, as well as the influence of motion artefacts, and electromagnetic noise. EMG can also be recorded using intramuscular detection systems, which allows the detection of electric potentials closer to the muscle fibres and the recording of EMG activity from deeper muscles. This paper evaluates the quality of intramuscular EMG recordings compared to surface EMG signals, as a preliminary step to control EMG-driven exoskeletons. Seven healthy subjects performed submaximal knee and ankle flexion/extension movements with and without the use of a lower limb exoskeleton. Intramuscular recordings presented early muscle activation detecting times, which is a very important feature in real-time control, and good signal-to-noise ratio values, showing the potential of these biosignals as reliable input measures to control exoskeletons for rehabilitation purposes.

Author

Camila Rodrigues

Spanish National Research Council (CSIC)

Marvin Fernandéz

San Pablo CEU University

Álvaro Megia

Hospital Nacional de Paraplejicos

Natalia Comino

Hospital Nacional de Paraplejicos

António Del-Ama

Hospital Nacional de Paraplejicos

Rey Juan Carlos University (URJC)

Ángel Gil-Agudo

Hospital Nacional de Paraplejicos

Moon Ki Jung

Imperial College London

Silvia Muceli

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Imperial College London

Dario Farina

Imperial College London

Juan Moreno

Cajal Institute

Jose L. Pons

Shirley Ryan AbilityLab

Northwestern University

Cajal Institute

Filipe O. Barroso

Cajal Institute

Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics

21551774 (ISSN)

Vol. 2020-November 564-569 9224361
9781728159072 (ISBN)

8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
New York City, USA,

Subject Categories

Physiotherapy

Other Medical Engineering

Physiology

Driving Forces

Sustainable development

Areas of Advance

Health Engineering

DOI

10.1109/BioRob49111.2020.9224361

More information

Latest update

6/8/2021 7