通过跟踪视频中的面部特征点来非接触式测量肌肉疲劳

Ramin Irani, Kamal Nasrollahi, T. Moeslund
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引用次数: 15

摘要

体育锻炼可能导致肌肉疲劳,即肌肉疲劳。当肌肉不能发挥正常的力量,或者当需要比正常更多的努力时,就会发生这种情况。疲劳是一个重要的信号,例如,当疲劳程度可能对病人有危险时,治疗师可以评估病人的进展,或者改变他们的锻炼方式。目前测量疲劳的技术,如肌电图(EMG),需要在身体上安装一些传感器。然而,在某些应用程序中,如远程患者监护,这可能是不可能的。针对这种情况,本文提出了一种基于计算机视觉技术的非接触式疲劳测量方法,通过检测、跟踪和分析运动过程中的一些面部特征点来测量疲劳。对多个被试的实验结果以及与地面真实数据的对比表明,所提出的系统能够较好地找到被试进行体育锻炼时肌肉的时间疲劳点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contactless measurement of muscles fatigue by tracking facial feature points in a video
Physical exercise may result in muscle tiredness which is known as muscle fatigue. This occurs when the muscles cannot exert normal force, or when more than normal effort is required. Fatigue is a vital sign, for example, for therapists to assess their patient's progress or to change their exercises when the level of the fatigue might be dangerous for the patients. The current technology for measuring tiredness, like Electromyography (EMG), requires installing some sensors on the body. In some applications, like remote patient monitoring, this however might not be possible. To deal with such cases, in this paper we present a contactless method based on computer vision techniques to measure tiredness by detecting, tracking, and analyzing some facial feature points during the exercise. Experimental results on several test subjects and comparing them against ground truth data show that the proposed system can properly find the temporal point of tiredness of the muscles when the test subjects are doing physical exercises.
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