Feature fusion analysis approach based on synchronous EEG-fNIRS signals: application in etomidate use disorder individuals.

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Tác giả: Chao Chen, Hongxian Chen, Yingwei Fan, Tianxin Gao, Bolin He, Qiuping Huang, Guangyao Liang, Zhenjiang Liao, Tefu Liu, Yuchen Ran, Xiaoying Tang

Ngôn ngữ: eng

Ký hiệu phân loại: 331.89041 Labor unions, labor-management bargaining and disputes

Thông tin xuất bản: United States : Biomedical optics express , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 171735

Etomidate is commonly used for induction of anesthesia, but prolonged use can affect brain neurovascular mechanisms, potentially leading to use disorders. However, limited research exists on the impact of etomidate on brain function, and accurately and noninvasively extracting and analyzing neurovascular brain features remains a challenge. This study introduces a novel feature fusion approach based on whole-brain synchronous Electroencephalography (EEG)-functional near-infrared spectroscopy (fNIRS) signals aimed at addressing the difficulty of jointly analyzing neural and hemodynamic signals and features in specific locations, which is critical for understanding neurovascular mechanism changes in etomidate use disorder individuals. To address the challenge of optimizing the accuracy of neurovascular coupling analysis, we proposed a multi-band local neurovascular coupling (MBLNVC) method. This method enhances spatial precision in NVC analysis by integrating multi-modal brain signals. We then mapped the different brain features to the Yeo 7 brain networks and constructed feature vectors based on these networks. This multilayer feature fusion approach resolves the issue of analyzing complex neural and vascular signals together in specific brain locations. Our approach revealed significant neurovascular coupling enhancement in the sensorimotor and dorsal attention networks (
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