首页> 外文会议>Biosignals and Biorobotics Conference (BRC), 2012 ISSNIP >Characterization and diagnosis of fibromyalgia based on fatigue analysis with sEMG signals
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Characterization and diagnosis of fibromyalgia based on fatigue analysis with sEMG signals

机译:基于sEMG信号疲劳分析的纤维肌痛特征与诊断

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Fibromyalgia (FM) is a chronic musculoskeletal disturbance that poses major challenges for diagnostic procedures. It is marked by a constellation of symptoms, such as widespread pain, chronic fatigue, sleep disturbances, osteoarthritis, among others. This work is a pilot study that aims to validate a diagnostic tool by analyzing sEMG signals of specific muscles during the performance of isotonic tasks. This work is a pilot study that aims to validate a diagnostic protocol with people affected by fibromyalgia. The objective was to indentify the behavior of five fatigue indicators: RMS, ARV, MNF, MDF and IAF, at 30%, 60% and 80% of MCV with a cutoff parameter k of 60%.
机译:纤维肌痛(FM)是一种慢性肌肉骨骼疾病,对诊断程序构成了重大挑战。它以一系列症状为特征,例如广泛的疼痛,慢性疲劳,睡眠障碍,骨关节炎等。这项工作是一项试点研究,旨在通过在执行等张任务期间分析特定肌肉的sEMG信号来验证诊断工具。这项工作是一项试点研究,旨在验证受纤维肌痛影响的人的诊断方案。目的是确定五个疲劳指标的行为:RMS,ARV,MNF,MDF和IAF,分别为MCV的30%,60%和80%,临界参数k为60%。

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