five

Data_Sheet_1_Bursting Rate Variability.zip

收藏
frontiersin.figshare.com2023-05-31 更新2025-01-15 收录
下载链接:
https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Bursting_Rate_Variability_zip/17109851/1
下载链接
链接失效反馈
官方服务:
资源简介:
In this paper, a new electromyographic phenomenon, referred to as Bursting Rate Variability (BRV), is reported. Not only does it manifest itself visually as a train of short periods of accrued surface electromyographic (sEMG) activity in the traces, but it has a deeper underpinning because the sEMG bursts are synchronous with wavelet packets in the D8 subband of the Daubechies 3 (db3) wavelet decomposition of the raw signal referred to as “D8 doublets”—which are absent during muscle relaxation. Moreover, the db3 wavelet decomposition reconstructs the entire sEMG bursts with two contiguous relatively high detail coefficients at level 8, suggesting a high incidence of two consecutive neuronal discharges. Most importantly, the timing between successive bursts shows some variability, hence the BRV acronym. Contrary to Heart Rate Variability (HRV), where the R-wave is easily identified, here, time-localization of the burst requires a statistical waveform matching between the “D8 doublet” and the burst in the raw sEMG signal. Furthermore, statistical fitting of the empirical distribution of return times shows a striking difference between control and quadriplegic subjects. Finally, the BRV rate appears to be within 60–88 bursts per minute on average among 9 human subjects, suggesting a possible connection between BRV and HRV.

本文报道了一种新的肌电图现象,被称为爆发率变异性(BRV)。此现象不仅在肌电图(sEMG)活动轨迹中表现为一系列短期的累积活动,而且其内在机理更为深刻,因为sEMG的爆发与原始信号Daubechies 3(db3)小波分解的D8子带中的小波包同步——这些小波包在肌肉松弛期间不存在。此外,db3小波分解以两个连续的相对高细节系数在8级上重建整个sEMG爆发,表明连续神经元放电的高发生率。最重要的是,连续爆发之间的时间间隔表现出一定的变异性,因此得名BRV。与心率变异性(HRV)不同,其中R波易于识别,在这里,爆发的时间定位需要“D8双峰”与原始sEMG信号中的爆发之间的统计波形匹配。此外,对返回时间的经验分布进行统计拟合显示,正常人和截瘫患者在控制方面存在显著差异。最后,在9名受试者中,BRV的爆发率平均在每分钟60至88次之间,这表明BRV与HRV之间可能存在某种联系。
提供机构:
Frontiers
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作