脑电图
语音识别
噪音(视频)
计算机科学
信噪比(成像)
功能连接
听力学
模式识别(心理学)
心理学
人工智能
神经科学
医学
电信
图像(数学)
作者
Payam Shahsavari Baboukani,Carina Graversen,Emina Aličković,Jan Østergaard
标识
DOI:10.1109/embc46164.2021.9630139
摘要
Comprehension of speech in noise is a challenge for hearing-impaired (HI) individuals. Electroencephalography (EEG) provides a tool to investigate the effect of different levels of signal-to-noise ratio (SNR) of the speech. Most studies with EEG have focused on spectral power in well-defined frequency bands such as alpha band. In this study, we investigate how local functional connectivity, i.e. functional connectivity within a localized region of the brain, is affected by two levels of SNR. Twenty-two HI participants performed a continuous speech in noise task at two different SNRs (+3 dB and +8 dB). The local connectivity within eight regions of interest was computed by using a multivariate phase synchrony measure on EEG data. The results showed that phase synchrony increased in the parietal and frontal area as a response to increasing SNR. We contend that local connectivity measures can be used to discriminate between speech-evoked EEG responses at different SNRs.
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