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TRV-2026-0801Certified recordPeer-reviewed

Automated autism spectrum disorder detection using EEG signals and time-frequency visibility graphs

Early and objective screening of Autism Spectrum Disorder (ASD) remains challenging because conventional diagnosis primarily relies on behavioural assessment and clinical observation. To address this limitation, this study proposes a dual-domain computational framework for automated EEG-based ASD classification by integrating complementary time-frequency analysis with Horizontal Visibility Graph (HVG)-based network modelling. Four time-frequency decomposition techniques, namely the Short-Time Fourier Transform (…

Health · G Space — documented gain · certified 2026-08-17 · v1 · article view · machine-readable

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A DWT-HVG framework with Soft Voting Ensemble enabled automated classification of resting-state EEG for ASD screening with 93.54% accuracy and 98.17% AUC in stratified 10-fold cross-validation.

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Truvace Impact Record TRV-2026-0801, v1: “Automated autism spectrum disorder detection using EEG signals and time-frequency visibility graphs.” Truvace, 2026-08-17. /record/TRV-2026-0801 (accessed at citation time). sha256 610ded5e93ad4466…

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