■表面肌电图(表面EMG)是通过表面电极检测肌肉电活动的主要技术。近年来,表面肌电图应用已经从传统领域发展到新领域。然而,表面肌电图的研究进展与临床接受之间存在差距,其特点是临床医生社区广泛使用表面肌电图的转化知识和技能。为了缩小这个差距,有必要将更新的表面肌电图应用和技术进步转化为临床研究。因此,我们旨在介绍表面肌电图和信号处理方法应用的最新进展。
■我们遵循JoannaBriggsInstitute(JBI)方法进行了这项范围审查。我们对PubMed和WebofScience进行了一般搜索,以确定关键搜索术语。搜索之后,我们将选定的文章上传到Rayyan并删除了重复项。在对133个标题和摘要进行预筛选后,我们根据纳入标准评估了91篇全文.
■我们得出结论,表面肌电图已经取得了创新性的技术进步,并且在常规临床应用和广泛的应用方面具有研究潜力,比如神经生理学,体育和艺术表演,生物反馈,物理治疗和康复,体育锻炼的评估,肌肉力量,疲劳,姿势和姿势控制,运动分析,肌肉协调,电机协同作用,建模,还有更多.新的方法已经在时域上应用于表面肌电信号,频域,时频域,统计方法,和非线性方法。
■将表面肌电图和信号分析方法的创新转化为常规临床应用可能是一种有用的工具,在临床实践中的肌肉激活测量中发挥着越来越重要的作用。因此,研究人员必须建立更多的接口,为继续教育和研究提供更现代的技术和设备的机会。
UNASSIGNED: Surface electromyography (surface EMG) is a primary technique to detect the electrical activities of muscles through surface electrodes. In recent years, surface EMG applications have grown from conventional fields into new fields. However, there is a gap between the progress in the research of surface EMG and its clinical acceptance, characterized by the translational knowledge and skills in the widespread use of surface EMG among the clinician community. To reduce this gap, it is necessary to translate the updated surface EMG applications and technological advances into clinical research. Therefore, we aimed to present a perspective on recent developments in the application of surface EMG and signal processing methods.
UNASSIGNED: We conducted this scoping review following the Joanna Briggs Institute (JBI) method. We conducted a general search of PubMed and Web of Science to identify key search terms. Following the search, we uploaded selected articles into Rayyan and removed duplicates. After prescreening 133 titles and abstracts, we assessed 91 full texts according to the inclusion criteria.
UNASSIGNED: We concluded that surface EMG has made innovative technological progress and has research potential for routine clinical applications and a wide range of applications, such as neurophysiology, sports and art performances, biofeedback, physical therapy and rehabilitation, assessment of physical exercises, muscle strength, fatigue, posture and postural control, movement analysis, muscle coordination, motor synergies, modelling, and more. Novel methods have been applied for surface EMG signals in terms of time domain, frequency domain, time-frequency domain, statistical methods, and nonlinear methods.
UNASSIGNED: Translating innovations in surface EMG and signal analysis methods into routine clinical applications can be a helpful tool with a growing and valuable role in muscle activation measurement in clinical practices. Thus, researchers must build many more interfaces that give opportunities for continuing education and research with more contemporary techniques and devices.