Diffusion Adaptive Filtering for Modelling Brain Responses to Motor Tasks

被引：0
|
作者：
Eftaxias, Konstantinos [1 ]
Sanei, Saeid [1 ]
机构：
[1] Univ Surrey, Dept Comp, Guildford GU2 5XH, Surrey, England
来源：
2013 18TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP) | 2013年
关键词：
Diffusion adaptation; brain connectivity; directed transfer function; Kalman filtering; brain-computer interface; INFORMATION-FLOW; CONNECTIVITY;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Diffusion adaptation combined with an adaptive way of estimating brain connectivity is used here in order to model specific motor tasks. We use Kalman filtering to fit an adaptive multivariate autoregressive model to our data and compute the connectivity measure which is a time-varying version of directed transfer function (DTF). The resulting method is used to classify the data from movement-related activities. The comparison between the proposed method and the non-diffusion method shows superiority of the former one.
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页数：5
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