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  • Data augmentation for generating synthetic electrogastrogram time series [Elektronski vir]
    Miljković, Nadica ...
    To address an emerging need for large number of diverse datasets for rigor evaluation of signal processing techniques, we developed and evaluated a new method for generating synthetic ... electrogastrogram time series. We used electrogastrography (EGG) data from an open database to set model parameters and statistical tests to evaluate synthesized data. Additionally, we illustrated method customization for generating artifcial EGG time series alterations caused by the simulator sickness. Proposed data augmentation method generates synthetic EGG data with specifed duration, sampling frequency, recording state (postprandial or fasting state), overall noise and breathing artifact injection, and pauses in the gastric rhythm (arrhythmia occurrence) with statistically signifcant diference between postprandial and fasting states in>70% cases while not accounting for individual diferences. Features obtained from the synthetic EGG signal resembling simulator sickness occurrence displayed expected trends. The code for generation of synthetic EGG time series is not only freely available and can be further customized to assess signal processing algorithms but also may be used to increase data diversity for training artifcial intelligence (AI) algorithms. The proposed approach is customized for EGG data synthesis but can be easily utilized for other biosignals with similar nature such as electroencephalogram.
    Vir: Medical & biological engineering & computing [Elektronski vir] : journal of the International Federation for Medical & Biological Engineering. - ISSN 1741-0444 (Vol. , iss. , 2024, [13] str.)
    Vrsta gradiva - e-članek ; neleposlovje za odrasle
    Leto - 2024
    Jezik - angleški
    COBISS.SI-ID - 194766851

    Povezava(-e):

    https://link.springer.com/article/10.1007/s11517-024-03112-0
    DOI

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