【24h】

FRAILTY ANALYSIS OF SEMG SIGNALS FOR DIFFERENT HAND MOVEMENTS BASED ON TEMPORAL AND SPECTRAL APPROACH

机译:基于时间和谱方法的不同手部运动SEMG信号的耐久性分析

获取原文

摘要

Surface electromyography (sEMG) signal is the electrical manifestation of neuromuscular activities. It is an intricatesignal that depends on the anatomical and physiological properties of the contracting muscles beneath the skin. In thiswork, a single channel surface EMG amplifier is designed to acquire the signals non-invasively from the skin by usingbio-potential electrodes for three different hand movements. Subjects of age group 1 (18-30 years) and group 2 (60-78years) are considered for this analysis. The recorded signals are pre-processed using Empirical Mode Decomposition(EMD) method to remove unwanted noises. Various error measures and performance index are calculated from thepre-processed sEMG signals to compare the performance of EMD with conventional digital filters. Relevant time andfrequency domain features are extracted from the pre-processed signals. It is observed that the statistical analysisperformed over the extracted features show distinct variation between the age groups. Thus the methodologyproposed in this work could be useful for the analysis of frailty especially for the subjects above 60 years.
机译:表面肌电图(sEMG)信号是神经肌肉活动的电表现。错综复杂 取决于皮肤下方收缩肌肉的解剖和生理特性的信号。在这个 工作时,单通道表面肌电图放大器被设计为通过使用以下方法从皮肤无创获取信号: 生物电位电极,用于三种不同的手部动作。 1岁组(18-30岁)和2组(60-78岁)的受试者 年)进行此分析。使用经验模式分解对记录的信号进行预处理 (EMD)方法来去除不需要的噪声。各种错误度量和性能指标是根据以下公式计算得出的: 预处理sEMG信号,以比较EMD与常规数字滤波器的性能。相关时间和 从预处理信号中提取频域特征。据观察,统计分析 在提取的特征上执行的操作显示了年龄组之间的明显差异。因此,方法论 这项工作中提出的建议可能对脆弱性的分析尤其有用,尤其是对于60岁以上的受试者。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号