Suppr超能文献

关于半周期叠加点过程的分离:应用于肌电信号

On the separation of semiperiodic superimposed point processes: application to electromyographic signals.

作者信息

Gath I

出版信息

Comput Programs Biomed. 1975 Mar;4(3):137-43. doi: 10.1016/0010-468x(75)90015-x.

Abstract

A method for the separation of semiperiodic (Gaussian probability distribution of intervals with moderate coefficient of variation) superimposed point processes, to be implemented on a digital computer is described. The efficiency of the filter used for the extraction of the underlying event sequences from the pooled array has been investigated by simulation. Approximately 80 percent of the events belonging to the underlying sequence to be extracted were recovered (with the addition of "impurity events"), still preserving the mean rate and coefficient of variation of the original indicidual sequence concerned. The program was used on an example of an actual electromyographic recording (comprised of a number of motor units discharging simultaneously), resolving the number of motor units involved, their mean rates, and the coefficient of variation of the individual action potential sequences.

摘要

本文描述了一种用于分离半周期(间隔呈高斯概率分布且变异系数适中)叠加点过程的方法,该方法将在数字计算机上实现。通过模拟研究了用于从合并数组中提取潜在事件序列的滤波器的效率。大约80%属于要提取的潜在序列的事件被恢复(同时添加了“杂质事件”),同时仍保留了原始相关个体序列的平均速率和变异系数。该程序应用于实际肌电图记录的一个示例(由多个同时放电的运动单位组成),解析出所涉及的运动单位数量、它们的平均速率以及各个动作电位序列的变异系数。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验