基于表面肌电图的可穿戴周围神经病变检测系统

Kainat Yousaf, Hamna Ather, Wala Saadeh
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引用次数: 1

摘要

周围神经病变是一种影响周围神经系统神经正常活动的疾病。周围神经病变患者受累部位可能有刺痛、麻木、异常感觉、无力或灼痛。这种疾病的患病率在土耳其为50%,在中东为22% -600%,在巴基斯坦为69%。我们的目的是设计一种简单可靠的方法来检测神经病变。肌电图(Electromyography, EMG)信号可用于医学异常分析和人体生物医学分析。这种信号携带着有关神经系统的宝贵信息。肌电图将被用来记录通过皮肤表面电极的电活动。本工作旨在通过对健康和震颤肌电信号的预处理、频响分析和处理等模块提取肌电信号。最后,我们将能够区分一个健康的人和一个患有疾病的人。预计肌电信号的分析将在震颤检测中有更广泛的应用和研究。
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Wearable Peripheral Neuropathy Detection System based on Surface Electromyography
Peripheral neuropathy is a condition that affects the normal activity of the nerves of the peripheral nervous system. Patients with peripheral neuropathy may have tingling, numbness, unusual sensations, weakness, or burning pain in the affected area. The prevalence of this ailment ranges from 50% in Turkey, 22-600% in the Middle East, and 69% in Pakistan. Our aim is to devise a simple and reliable method to detect neuropathy. The Electromyography (EMG) signal can be used to analyze medical abnormalities and to analyze the bio medics of the human body. The signal carries valuable information regarding the nerve system. The electromyogram will be used to record the electrical activity through the surface electrodes applied to the skin. This work aims to extract the EMG signal through various modules: pre-amplification, frequency response analysis and processing of the signal extracted from both healthy and the ones with the tremor. At the end, we will be able to differentiate a healthy person from the one suffering from the ailment. It is supposed that the analysis of EMG signal will have wider application and research of tremor detection.
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