Myoelectric Interfaces and Related Applications: Current State of EMG Signal Processing–A Systematic Review

Bernabe Rodriguez-Tapia,Daniela M Martinez,Israel Soto,Norma Candolfi Arballo

doi:10.1109/access.2019.2963881

Bernabe Rodriguez-Tapia, Daniela M Martinez + Show 2 more

Open Access

https://doi.org/10.1109/access.2019.2963881

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Abstract

The myoelectric interfaces are being used in rehabilitation technology, assistance and as an input device. This review focuses on an insightful analysis of the data acquisition system of EMG signals from these interfaces. According to applications reported in research articles of the last five years, the properties of the sensors, the number of channels, the pre-processing of the EMG signal, as well as the software and hardware used were identified. This analysis was performed for the following applications: monitoring of muscular activation for rehabilitation, muscle activation plans, and identification of possible pathologies, exoskeletons, electric of wheelchairs, prosthetics control, myoelectric bracelets, handwriting recognition and silent speech recognition. The results presented in this review become a guide of recommendations for the myoelectric signal processing according to the application of the interface. The main developments, degrees of research and open challenges are also presented in this direction.

Highlights

Electromyography (EMG) is a technique used to measure the muscle’s response to electrical stimulus of the nerves [1]
It is important to note that there is a significant amount of publications in the field, only a small number of publications address the specifications regarding the design of EMG signal acquisition systems
The aforementioned applications are classified by Hakonen [18] into three categories: (1) Rehabilitative technology, that includes activation of exoskeletons and monitoring of muscle activation which is useful for the detection and prevention of health problems, as well as for activation and strengthening of muscular structures; (2) assistive technology, involving the control of prosthetics and motorized wheelchairs by means of EMG signals; and (3) technology as an input device, which includes the use of myoelectric bracelets for the identification of gestures or sign language, myoelectric interfaces for writing interpretation and sketching, and myoelectric sensors for silent speech recognition

Summary

Introduction

Electromyography (EMG) is a technique used to measure the muscle’s response to electrical stimulus of the nerves [1]. The EMG signal acquired from the skin surface around muscle and joint areas is the summation of the electrical activity of all the muscle-fibred motor unit action potentials (MUAPs) caused as a result of motion activity [2]. EMG signals have been relevant in several health fields. The periodical monitoring of EMG signals can be utilized to detect diseases like Huntington’s disease, Myopathies, or Muscular dystrophies, and to timely address problems such as heart attacks or stroke occur [3], [4]. EMG signals could be useful to detect neuromuscular disorders that could affect motor units (Mus) and to identify the origin of such disorders [5]. In the HumanComputer Interaction (HCI) field, the use of bio signals has opened the way for the development of muscle-computer interfaces.

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