IEEE J Biomed Health Inform. 2015 Sep;19(5):1672-81. doi: 10.1109/JBHI.2014.2356340. Epub 2014 Sep 8.
Sport, fitness, as well as rehabilitation activities, often require the accomplishment of repetitive movements. The correctness of the exercises is often related to the capability of maintaining the required cadence and muscular force. Failure to maintain the required force, also known as muscle fatigue, is accompanied by a shift in the spectral content of the surface electromyography (EMG) signal toward lower frequencies. This paper presents a novel approach for simultaneously obtaining exercise repetition frequency and evaluating muscular fatigue, as functions of time, by only using the EMG signal. The mean frequency of the amplitude spectrum (MFA) of the EMG signal, considered as a function of time, is directly related to the dynamics of the movement performed and to the fatigue of the involved muscles. If the movement is cyclic, MFA will display the same pattern and its average will tend to decrease. These two effects have been simultaneously modeled by a two-component AM-FM model based on the Hilbert transform. The method was tested on signals recorded using a wireless system applied to healthy subjects performing dumbbell biceps curls, dumbbell lateral rises, and bodyweight squats. Experimental results show the excellent performance of the proposed technique.
运动、健身和康复活动通常需要完成重复的动作。运动的正确性通常与保持所需的节奏和肌肉力量的能力有关。如果无法保持所需的力量（即肌肉疲劳），则表面肌电图（EMG）信号的频谱内容会向低频转移。本文提出了一种新的方法，仅使用 EMG 信号即可同时获得运动重复频率和肌肉疲劳随时间变化的评估。将 EMG 信号的幅度谱均值频率（MFA）视为时间的函数，它与所执行运动的动态和相关肌肉的疲劳直接相关。如果运动是周期性的，MFA 将显示相同的模式，其平均值将趋于下降。这两种效果都通过基于希尔伯特变换的两分量 AM-FM 模型同时进行建模。该方法已在使用无线系统记录的信号上进行了测试，该系统应用于进行哑铃二头肌卷曲、哑铃侧举和自重深蹲的健康受试者。实验结果表明，该技术具有出色的性能。
