结合脑电图和心电信号检测癫痫发作的时频域特征评估

Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments Pub Date : 2014-05-27 DOI:10.1145/2674396.2674412

I. Mporas, Vasiliki Tsirka, E. Zacharaki, M. Koutroumanidis, V. Megalooikonomou

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引用次数: 14

摘要

本文对脑电图和心电图信号的时域和频域特征进行了大规模评估，用于癫痫发作检测。对于分类，我们依赖于支持向量机算法。对三个被试的癫痫检测架构进行了评估，其中两个被试的检测准确率超过90%，第三个被试的检测准确率略低于90%。

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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Evaluation of time and frequency domain features for seizure detection from combined EEG and ECG signals

In this paper, a large scale evaluation of time-domain and frequency domain features of electroencephalographic and electrocardiographic signals for seizure detection was performed. For the classification we relied on the support vector machines algorithm. The seizure detection architecture was evaluated on three subjects and the achieved detection accuracy was more than 90% for two of them and slightly lower than 90% for the third subject.

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来源期刊

Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments

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