Multi-scale transformation-based image representation and analysis of amplitude-integrated EEG

Wenjing Wu; Weiting Chen; Yujiao Hu

doi:10.1117/12.2687777

28 August 2023 Multi-scale transformation-based image representation and analysis of amplitude-integrated EEG

Wenjing Wu, Weiting Chen, Yujiao Hu

Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 1272406 (2023) https://doi.org/10.1117/12.2687777
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China

Abstract

Amplitude-integrated electroencephalography (aEEG) is widely adopted for recognizing neonatal neurological disorders in clinics. Previous work has mainly analyzed aEEGs from a time series perspective, while clinicians are more concerned about images. This paper studies the efficacy of image representations in aEEG interpretation. To this end, we employ Amplitude-frequency contour map (AFCM) to express information on local amplitude distributions and overall temporal trend. During its generation, Multi-scale Box-Cox transformation is introduced to flexibly control the degree of amplitude compression and capture details in different amplitude regions. Moreover, one- and two-dimensional features are extracted and combined to enhance model predictions. The experimental results show the potential of image representation for aEEG recognition. This method can provide new ideas to analyze time series signals like aEEGs from the perspective of combining time series and image.

Citation Download Citation

Wenjing Wu, Weiting Chen, and Yujiao Hu "Multi-scale transformation-based image representation and analysis of amplitude-integrated EEG", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 1272406 (28 August 2023); https://doi.org/10.1117/12.2687777

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