Temporal Patterns Analysis in EEG Data using Sonification

Z. Halim, R. Baig, S. Bashir
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引用次数: 8

Abstract

Brain computer interfacing is a direct communication pathway between human and computer. The area is innovative and under active research as a subset of human computer interaction. Brain computer interfacing typically utilize electroencephalogram (EEG) data to apply machine learning and or computational intelligence techniques to trigger actions. Electroencephalogram data is a multivariate time series data whose visualization suffers from problems like cluster overlapping and high dimensionality. In this paper we present a natural alternative to visualization i.e. sonification. Thus combining the two novel area of research to explore and get better results over the conventional approaches. Sonification is the use of non-speech audio to convey information. We have presented a technique to sonify alpha, beta and gamma bands present in the Electroencephalogram data. Experiments have been performed on EEG data of a controlled subject and the results have been discussed at the end.
用超声分析脑电图数据的时间模式
脑机接口是人与计算机之间的直接通信途径。该领域是创新的,作为人机交互的一个子集,正在积极研究中。脑机接口通常利用脑电图(EEG)数据来应用机器学习和/或计算智能技术来触发动作。脑电图数据是一种多变量时间序列数据,其可视化存在聚类重叠、高维等问题。在本文中,我们提出了一个自然替代的可视化,即超声。从而结合两种新颖的研究领域进行探索,并获得优于传统方法的结果。声音化是利用非语音音频来传递信息。我们提出了一种对脑电图数据中的α、β和γ波段进行超声处理的技术。最后对实验对象的脑电图数据进行了实验,并对实验结果进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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