Artificial Intelligence Techniques for Biosignal Pattern Recognition and Classification in Upper-Limb Prostheses: A Review

Abstract

Currently, disability is a condition in which people are considered to have long-term physical, mental, intellectual, or sensory impairments due to different circumstances or situations, which may be due to an accident, illness, among others. According to the United Nations (UN), approximately 10% of people (650 million approximately) are registered with some type of disability, which is increasing due to population growth worldwide, medical advances and the aging process. Upper limb prostheses are devices that replace parts of the body of a person or user with upper limb disability or amputation, such as the arm, hand, among others. In this review, various Artificial Intelligence (AI) techniques were examined for their applications such as pattern recognition and classification of biosignals in a total of 72 upper limb prostheses in different categories such as the commercial name or main author’s name of the device, the characteristics of the patient-user who will use it, the level of amputation, the mechanism which is the body part that replaces the bionic hand, the control biosignals that activate the operation of the prosthesis, the Artificial Intelligence (AI) methods that have been employed, the applications of AI techniques and the Technology Readiness Level (TRL), which is the level of development of the upper limb prosthesis between the lowest level (1) and the highest level (9).