Hot topics and international frontiers of electromyography in the field of body movements

doi:10.12307/2022.1009

Abstract

Abstract: BACKGROUND: Electromyography (EMG) is widely used in the measurement of human limb movement or muscle activity, and it has been widely recognized by experts and scholars in the fields of medicine, sports science, and ergonomics. However, review papers on the application of EMG in human limb movements are slightly insufficient.
OBJECTIVE: To understand and comb the relevant EMG data in human limb movements from the Web of Science core database, attempting to further optimize the schematic design using EMG in human rehabilitation and ergonomics.
METHODS: Literature search with subject terms was performed in Web of Science Core Collection database based on Boolean logic operation. Search strategy was as follows: TS=“electromyography” OR “sEMG” OR “surface EMG” and “human movement” or “movement”. Included documents de-duplicated using the Citespace V were analyzed in terms of disciplines and countries. Hot topics and international frontier trends of relevant research were analyzed using the knowledge graph in terms of keywords, high citations, and co-citations.
RESULTS AND CONCLUSION: (1) Literature regarding the application of surface EMG in human limb movements is mainly published in the fields of neurology, engineering and sports science. Top three countries with the most publications are the United States, China, and Canada in order. (2) EMG application in human limb movement mainly focus on myoelectric control, chronic low back pain, corticospinal excitability, Parkinson’s disease, attentional focus, stroke survivor, anterior cruciate ligament injury, and muscle synergies. (3) International frontier research is divided into early frontier and modern frontier. Transition between the early and modern frontiers is from the fields of EMG control, EMG influencing factors and EMG algorithms to human-computer interaction and ergonomics (prosthetic rehabilitation). (4) EMG provides EMG parameter diagnosis in the fields of ergonomics, exercise biomechanics (muscle activation degree and time), evaluation of action mode, fatigue standard, and evaluation of rehabilitation training effects. There are significant differences in the recovery time, size and symmetry of trunk EMG in patients with stroke. EMG remains to be further studied in revealing the mechanism of unilateral limb resistance training in patients with stroke in response to activation of untrained limbs.

Key words: electromyography, body movement, SCI journal, SCI literature, frontier, hot spot, visualization

CLC Number:

Liu Yang, Zhu Zhiqiang, Zhao Xiaowei, Xiang Yujie, Xiao Jian, Cheng Lifen. Hot topics and international frontiers of electromyography in the field of body movements[J]. Chinese Journal of Tissue Engineering Research, 2022, 26(35): 5707-5715.

Figures/Tables 8

第1聚类：肌电控制(myoelectric control)，该聚类探究的是提取、预处理、处理原始肌电信号的方法，如现阶段工程学领域的肌电数据识别提取方法等工程学研究不断深入或利用机器学习[9]、深度学习(deep learning)[10]、模式识别(pattern recognition)以及各种人体运动中测量方法和文献不断出现。相关研究报道为肌电图应用寻找处理肌电数据方法提供文献支撑和参考，如采用非负矩阵因式分解法，从不同肌肉的肌电图数据中提取肌肉协同效应的方法[11]。第2聚类：慢性下腰痛(chronic low back pain)[12-17]，该聚类关注躯干肌肉活动(trunk muscle activity)；下腰痛(low back pain)；预期姿势调整(anticipatory postural adjustment)；背部疼痛(back pain)等相关研究，这些关键词主要针对职业病/办公室人群或者腰部损伤人群相关报道。第3聚类：皮质脊髓兴奋性(corticospinal excitability)[18-27]，人类脊髓损伤(human spinal cord injury)等关键词[28]，这些关键词是表面肌电技术测量应用到人体康复、假肢等领域。第4聚类：帕金森病(Parkinson’s disease)[29-36]，面部肌肉激活模式(facial muscle activation pattern)，节律性肌肉活动(rhythmic muscle activity)，运动性震颤(kinetic tremor)，自主收缩(voluntary movement)等关键词，这些关键词聚类主要关注患有神经系统疾病节律性肌肉活动帕金森病患者治疗和机制研究。第5聚类：注意焦点状态(attentional focus)[37-41]，同在一个类中有神经肌肉激活(neuromuscular activation)，如不同注意焦点状态对肌肉抗阻活动的影响，评价肌肉力量和训练经验对肌肉活动的可能影响。一般来说，内部注意力集中已经被证明可以增强对运动的有意识控制，从而在运动系统中诱发“噪音”。第6聚类：脑卒中存活患者(stroke survivor)[10，42-47]，脑卒中后患者(post-stroke patient)[48]，慢性脑卒中(chronic stroke)。此关键词聚类，关注中风患者的电刺激或者训练后干预情况，近些年备受专家、学者关注。第7聚类：前交叉韧带(anterior cruciate ligament injury，简称ACL)损伤[49-54]，该聚类探究关注肌电关注膝关节损伤，以及生物力学分析(biomechanical analysis)[55]，表面肌电信号(sEMG)具有分析人体下肢运动能力，包括人类步态步态评估(human gait)和关节角度估计等，可以为人体与外骨骼矫形器的交互作用提供高水平支持。第8聚类：肌肉协同(muscle synergies)[56-63]，健康人动作控制(healthy human | motor control)；神经力学适应(neuromechanical adaptation)，环境依赖性变化(context-dependent change)；健康成人(healthy adult)，肌肉力量(muscle force)[48]。肌肉协同和动作控制方面研究如在运动过程中利用多通道肌电记录仪将肌电记录下来，然后根据运动中每块肌肉放电顺序和肌电幅度，结合高速摄像等技术，对人体动作进行评估和诊断[64]。 2.3 国际研究前沿分析 2.3.1 共被引文献图谱分析节点类型(Node Types)选择Reference 时间分割(time slicing)选择1年，阈值项选择“Top N per slice”，节点阈值设定为每个切片中频次最高的50。在控制面板中，阈值(Threshold)设置25，字体大小(font size)设置为5，节点(node size)设置200，运行Citespace软件后共得到节点n=925，E=2 374，Q=0.382 6 > 0.3，生成图5。 "

(1)早期研究前沿(2010-2016)：重点关注表面肌电图的整体特征与潜在的生理过程之间的关系研究[65]，多数文献存在学术争议包括肌电采集、处理的方法(线性、非线性肌电信号处理)以及到肌电信号的检测、处理、分类和指标选择(RMS、IEMG、MDF…等)。肌电信号由原始生物电信号和干扰噪声信号组成，原始肌电图的振幅可以通过滤波、平滑和重新线性化的方案来进行处理，如利用小波分析或者因子分解算法提取原始生物电信号[66]。原始肌电信号处理也受很多因素的影响，如噪声干扰(检测仪器、环境电磁0-60 Hz低频部分)、电极粘贴方法如电极间距离[67]、采样时姿势、电阻影响、动作方式(解剖和生理)、脂肪厚度、性别与年龄、容积传导等等对原始肌电信号影响较大。由于多数肌电控制方案都利用了表面肌电的宏观特征，而这些特征又依赖于信号中所包含的神经和外周信息，其表现受到影响动作电位形状或神经驱动到肌肉因素的影响[65]。电极对重新定位、电极-皮肤之间阻抗变化(如出汗、毛发)、肌肉与电极相对运动因素包括肌纤维拉长、缩短或向心、离心收缩时的解剖学位置变化影响肌电信号采集。受试者个体之间动作电位形状的分布存在差异，不同肌肉、个体之间比较时，要注意进行肌电均方根值标准化。依据研究方案设计不同，表面肌电图时域、频域分析方法有较大差异。除了上述因素，较多影响因素不是直观的，肌电设备进行人体肢体动作试验时要特别注意肌电设备操作条件，规避影响肌电图/信号的因素，保证表面肌电信息采集客观性以及分析的准确性。 (2)最新研究前沿(2017-2021)：肌电图最新前沿领域研究在商业和临床研究有较多延伸。肌萎缩性脊髓侧索硬化症(Amyotrophic lateral sclerosis，简称渐冻症)、脑干中风、脑或脊髓损伤、脑瘫、肌肉营养不良、多发性硬化症和许多其他疾病会损害控制肌肉的神经通路或损害运动细胞。那些受影响最严重的患者可能会失去所有的自主肌肉控制能力，并可能完全锁定在身体内，无法以任何方式进行交流。现代生命支持技术可以让大多四肢瘫痪/残疾患者，能够更好地适应生活，让他们能与外界进行互动、减轻痛苦。假肢或者辅助性设备是利用人机交互界面的肌电信号实现神经康复辅助设备的控制，在研究过程中，利用肌电设备探测大脑和其他脊髓上区域[68]、周围神经或肌组织接口肌电信号信息得以实现人机交互，如通过采集正常人体肌肉活动动作的表面肌电活动信号信息来设计假体肌电信号模式[69]，或制作假肢肌电激活数学模型进行人机功效学等领域探索[70-71]。 "

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