Surface electromyography (EMG) comprises a recording of electrical activity from the body surface generated by muscle fibres during muscle contractions. Its characteristics depend on the fibre membrane potentials and the neural activation signal sent from the motor neurons to the muscles. EMG has been classically used as the primary investigation tool in kinesiology studies in a variety of applications. More recently, surface EMG techniques have evolved from single-channel methods to high-density systems with hundreds of electrodes. High-density EMG recordings can be deconvolved to estimate the discharge times of spinal motor neurons innervating the recorded muscles, with algorithms that have been developed and validated in the last two decades. Within limits and with some variability across muscles, these techniques provide a non-invasive method to study relatively large populations of motor neurons in humans. Surface EMG is thus evolving from a peripheral measure of muscle electrical activity towards a neural recording and neural interfacing signal. These advances in technology have had a major impact on our fundamental understanding of the neural control of movement and have exposed new perspectives in neurotechnologies. Here we provide an overview and perspective of modern EMG technology, as derived from past achievements, and its impact in neurophysiology and neural engineering.

表面肌电图 (EMG) 包括记录肌肉收缩过程中肌纤维产生的体表电活动。其特性取决于纤维膜电位和从运动神经元发送到肌肉的神经激活信号。肌电图通常被用作各种应用中运动机能学研究的主要研究工具。最近，表面肌电图技术已经从单通道方法发展到具有数百个电极的高密度系统。使用过去二十年开发和验证的算法，可以对高密度肌电图记录进行去卷积，以估计支配记录的肌肉的脊髓运动神经元的放电时间。在有限的范围内，并且在肌肉之间存在一定的变异性，这些技术提供了一种非侵入性的方法来研究人类相对较大的运动神经元群体。因此，表面肌电图正在从肌肉电活动的外周测量演变为神经记录和神经接口信号。这些技术进步对我们对运动神经控制的基本理解产生了重大影响，并揭示了神经技术的新观点。在这里，我们从过去的成就中总结出现代肌电图技术的概述和观点，及其对神经生理学和神经工程的影响。