基于人体下肢表肌电信号的疲劳等级分类系统设计

Kai Zhao, Jian Guo, Shuxiang Guo, Qiang Fu
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引用次数: 2

摘要

随着中国人口老龄化的加深,越来越多的人患中风。脑卒中具有高发病率、高死亡率、高致残率三大特点。目前,中风已经成为人类死亡的主要原因之一,而且在中国中风患者的人群逐渐年轻化,很多患者无法正常工作和生活,破坏了很多幸福的家庭。然而,中风并不是不可战胜的。患者一旦中风,只要积极进行康复训练,仍然可以独立生活和工作。表面肌电信号含有丰富的生理信息,在神经康复和骨科康复中具有显著的作用。康复训练较少的患者训练不能起到康复效果,过度训练容易造成二次损伤,因此,本文将设计一种基于人体下肢肌肉表肌电信号的疲劳状态分类系统,通过采集人体下肢目标肌肉表肌电信号来分析患者下肢的疲劳状态。确保患者既能进行有效的训练,又不会因过度训练而造成二次损伤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of Fatigue Grade Classification System Based on Human Lower Limb Surface EMG Signal
With the deepening of the aging of China’s population, more and more people suffer from stroke. Stroke has three characteristics: high morbidity, high mortality, and high disability rate. At present, stroke has become one of the main causes of human death, and the population suffering from a stroke in China is gradually becoming younger, many patients can not work and live normally, destroying many happy families. However, stroke is not invincible. Once suffering from stroke, patients can still live and work independently as long as they actively carry out rehabilitation training. The surface EMG signal contains abundant physiological information and has remarkable effects on nerve rehabilitation and orthopedic rehabilitation. Patients with rehabilitation training less training can not play a rehabilitation effect, and excessive training is easy cause secondary injuries, therefore, this paper will design a fatigue state classification system based on surface EMG signals of human lower limb muscles, and analyze the fatigue state of patients’ lower limbs by collecting surface EMG signals of target muscles of human lower limbs, to ensure that patients can not only carry out effective training but also not cause secondary injuries due to excessive training.
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