脑电和肌电信号处理中移动方差计算的记忆和处理高效公式

M. M. Krell, M. Tabie, Hendrik Wöhrle, E. Kirchner
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引用次数: 9

摘要

通过生理数据调整人机交互设备需要在线分析。我们引入了新的更新公式,否则需要时间计算基于窗口的电流均值和方差的信号。这些是有效的实时时间序列数据处理所必需的。我们借助综合数据对公式进行了讨论。它们不同于现有的增量计算,因为有一个递减分量,因为样本离开了观察窗口。给出了一个基于肌电图的运动开始预测的应用实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Memory and Processing Efficient Formula for Moving Variance Calculation in EEG and EMG Signal Processing
Adaptation of human-machine interaction devices by means of physiological data requires online analysis. We introduce new update formulas for otherwise time-demanding calculations of window based current mean and variance of the signal. Those were required for efficient realtime time series data processing. We discuss the formulas with the help of synthetic data. They differ from existing incremental calculations due to a decremental component, because of samples leaving the window of observation. An example application for EMG-based movement onset prediction is presented.
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