Suppr超能文献

应用于步态分析的表面肌电图:如何提高其在临床中的影响力?

Surface Electromyography Applied to Gait Analysis: How to Improve Its Impact in Clinics?

作者信息

Agostini Valentina, Ghislieri Marco, Rosati Samanta, Balestra Gabriella, Knaflitz Marco

机构信息

PoliToBIOMedLab, Politecnico di Torino, Turin, Italy.

Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.

出版信息

Front Neurol. 2020 Sep 4;11:994. doi: 10.3389/fneur.2020.00994. eCollection 2020.

Abstract

Surface electromyography (sEMG) is the main non-invasive tool used to record the electrical activity of muscles during dynamic tasks. In clinical gait analysis, a number of techniques have been developed to obtain and interpret the muscle activation patterns of patients showing altered locomotion. However, the body of knowledge described in these studies is very seldom translated into routine clinical practice. The aim of this work is to analyze critically the key factors limiting the extensive use of these powerful techniques among clinicians. A thorough understanding of these limiting factors will provide an important opportunity to overcome limitations through specific actions, and advance toward an evidence-based approach to rehabilitation based on objective findings and measurements.

摘要

表面肌电图(sEMG)是用于记录动态任务期间肌肉电活动的主要非侵入性工具。在临床步态分析中,已经开发了多种技术来获取和解释运动改变患者的肌肉激活模式。然而,这些研究中描述的知识体系很少转化为常规临床实践。这项工作的目的是批判性地分析限制这些强大技术在临床医生中广泛应用的关键因素。深入了解这些限制因素将提供一个重要机会,通过采取具体行动克服限制,并朝着基于客观发现和测量的循证康复方法迈进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59b9/7502709/123ada683642/fneur-11-00994-g0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验