Muscle fatigue represents a complex physiological and psychological phenomenon that impairs physical performance and increases the risks of injury. It is important to continuously monitor fatigue levels for early detection and management of fatigue. The detection and classification of muscle fatigue also provide important information in human-computer interactions (HMI), sports injuries and performance, ergonomics, and prosthetic control. With this purpose in mind, this review first provides an overview of the mechanisms of muscle fatigue and its biomarkers and further enumerates various non-invasive techniques commonly used for muscle fatigue monitoring and detection in the literature, including electromyogram (EMG), which records the muscle electrical activity during muscle contractions, mechanomyogram (MMG), which records vibration signals of muscle fibers, near-infrared spectroscopy (NIRS), which measures the amount of oxygen in the muscle, ultrasound (US), which records signals of muscle deformation during muscle contractions. This review also introduces the principle and mechanism, parameters used for fatigue detection, application in fatigue detection, and advantages and disadvantages of each technology in detail. To conclude, the limitations/challenges that need to be addressed for future research in this area are presented.

肌肉疲劳是一种复杂的生理和心理现象，会损害身体机能并增加受伤的风险。持续监测疲劳程度对于及早发现和管理疲劳非常重要。肌肉疲劳的检测和分类还为人机交互 (HMI)、运动损伤和表现、人体工程学和假肢控制提供重要信息。出于这个目的，本文首先概述了肌肉疲劳的机制及其生物标志物，并进一步列举了文献中常用的各种用于肌肉疲劳监测和检测的非侵入性技术，包括肌电图（EMG），它记录了肌肉疲劳的情况。肌肉收缩期间的肌肉电活动、记录肌纤维振动信号的肌力图 (MMG)、测量肌肉中氧含量的近红外光谱 (NIRS)、记录肌肉收缩过程中肌肉变形信号的超声波 (US)肌肉收缩。本文还详细介绍了疲劳检测的原理和机制、疲劳检测所用的参数、在疲劳检测中的应用以及每种技术的优缺点。总之，提出了该领域未来研究需要解决的局限性/挑战。