一种基于个体的常规空间肌电信号时域特征的新方法

Vineeth K Kumar
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引用次数: 6

摘要

为了对观测得到的任何一组数值数据得出合适的结论和做出合理的决策,需要用不同的方法对其进行聚类,以确定其唯一的值。这种独特的价值通过不同的方式赋予了整个群体的代表性价值,人类更容易把握。求群唯一值的方法有均值、均值绝对值、均方根、简单平方积分等。本文还讨论了在连续域和离散域的常规个体空间(2)上求数据唯一值的几种不同方法。对于这样的函数,拆分是必需的。函数分裂背后的目的是将其分成两部分,作为积极或消极的部分,以便在个体相似性的基础上分析数据。到目前为止,在大多数情况下,通过不同的方式进行数据分析,我们只是在集体的基础上进行的,但在这里,我们有一种方法来分析相同的,但在个人的基础上,因为它提供了额外的信息,这可能被证明是有益的,在某些情况下,如表面肌电信号分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new proposal for time domain features of EMG signal on individual basis over conventional space
To draw suitable conclusion(s) and make rational decision(s) on any set of numerical data obtained from observations, the bunching of it is require by ways of different to determine the unique value for it. This unique value by ways of different gives the representative value of the whole group, which human can grasp more easily. The different ways for finding the unique value of a group are mean, mean absolute value, RMS, simple square integral etc. In this paper also, some of the different ways for finding of unique value of a data are discuss but over the conventional space of individuals, which is 2, in case of both continuous and discrete domain. For such function splitting is require. The objective behind the function splitting is to make it in to the parts of two as a positive or negative to analyze the data on individual similarity basis. Up till in most of the cases of data analyzing by ways of different we are doing it on the collective basis only, but here we have the approach for analyzing the same but on individual basis as well, as it provides additional information, which may proves to be beneficial in some cases like surface EMG classification.
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