{"title":"A survey on hand gesture recognition based on surface electromyography: Fundamentals, methods, applications, challenges and future trends","authors":"","doi":"10.1016/j.asoc.2024.112235","DOIUrl":null,"url":null,"abstract":"<div><p>Hand gestures are crucial for developing prosthetic and rehabilitation devices, enabling intuitive human–computer interaction (HCI) and improving accessibility for individuals with impairments. Recently, gesture recognition systems based on surface electromyography (sEMG) have been widely employed in various fields, demonstrating remarkable advantages and developments. In this paper, we present a comprehensive survey on sEMG-based hand gesture recognition. We provide an overview of the basic knowledge and background of sEMG signals and the acquisition equipment used. We delve into the applied feature extraction methods and classification models, focusing on recent advances in deep learning techniques. We also identify the datasets of sEMG signals used for hand gesture recognition. Moreover, we highlight recent applications of sEMG-based gesture recognition methods, including HCI, sign language recognition, rehabilitation, prosthesis control, and exoskeletons for augmentation. Additionally, we outline the latest innovative progress in this field, such as the influence of force, user identity detection, and migration effects. We also discuss the current limitations and challenges. Finally, we summarize the main findings and discuss future directions to enhance sEMG-based hand gesture recognition.</p></div>","PeriodicalId":50737,"journal":{"name":"Applied Soft Computing","volume":null,"pages":null},"PeriodicalIF":7.2000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Soft Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1568494624010093","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Hand gestures are crucial for developing prosthetic and rehabilitation devices, enabling intuitive human–computer interaction (HCI) and improving accessibility for individuals with impairments. Recently, gesture recognition systems based on surface electromyography (sEMG) have been widely employed in various fields, demonstrating remarkable advantages and developments. In this paper, we present a comprehensive survey on sEMG-based hand gesture recognition. We provide an overview of the basic knowledge and background of sEMG signals and the acquisition equipment used. We delve into the applied feature extraction methods and classification models, focusing on recent advances in deep learning techniques. We also identify the datasets of sEMG signals used for hand gesture recognition. Moreover, we highlight recent applications of sEMG-based gesture recognition methods, including HCI, sign language recognition, rehabilitation, prosthesis control, and exoskeletons for augmentation. Additionally, we outline the latest innovative progress in this field, such as the influence of force, user identity detection, and migration effects. We also discuss the current limitations and challenges. Finally, we summarize the main findings and discuss future directions to enhance sEMG-based hand gesture recognition.
期刊介绍:
Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities.
Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.