基于频谱F检验的多变量诱发反应检测。

Multivariate evoked response detection based on the spectral F-test.

作者信息

Rocha Paulo Fábio F, Felix Leonardo B, Miranda de Sá Antonio Mauricio F L, Mendes Eduardo M A M

机构信息

Departamento de Engenharia Elétrica, Universidade Federal de Viçosa, Av. PH Rolfs, SN, 36570-900 Viçosa, MG, Brazil; Programa de Pós-graduação em Engenharia Elétrica, Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, 31270-901 Belo Horizonte, MG, Brazil.

Departamento de Engenharia Elétrica, Universidade Federal de Viçosa, Av. PH Rolfs, SN, 36570-900 Viçosa, MG, Brazil.

出版信息

J Neurosci Methods. 2016 May 1;264:113-118. doi: 10.1016/j.jneumeth.2016.03.005. Epub 2016 Mar 11.

DOI:10.1016/j.jneumeth.2016.03.005

PMID:26976723

Abstract

BACKGROUND

Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal.

NEW METHOD

Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed.

RESULTS

The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector.

COMPARISON WITH EXISTING METHOD(S): The multivariate method showed detection rates consistently higher than those ones when only one signal was used.

CONCLUSIONS

It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used.

摘要