Artificial intelligence based on fuzzy logic for the analysis of human movement in healthy people: a systematic review

Original article was published by on Latest Results for Artificial Intelligence Review

Abstract

Technological advances that involve computing and artificial intelligence (AI) have led to advances in analysis methods. Fuzzy logic (FL) serves as a qualitative interpretation tool for AI. The objective of this systematic review is to investigate the methods of human movement (HM) analysis using AI through FL to understand the characteristics of the movement of healthy people. To identify relevant studies published up to April 19, 2019, we conducted a study of the PubMed, Scopus, ScienceDirect, and IEEE Xplore databases. We included studies that evaluated HM through AI using FL in healthy people. A total of 951 articles were examined, of which six were selected because they met the criteria presented in the methods. The protocols had high heterogeneity, yet all articles selected presented statistically satisfactory results, in addition to low errors or a false positive index. Only one selected article presented protocol applicability within the free-living model. Generally, AI using FL is a good tool to help assess HM in healthy people, but the model still needs new data acquisition entries to make it applicability within the free-living model.