Novel accurate classification system developed using order transition pattern feature engineering technique with physiological signals

Abstract This paper presents a novel, explainable feature engineering framework for classifying EEG and ECG signals with high accuracy. The proposed method employs the Order Transition Pattern (OTPat) feature extractor. The presented OTPat feature extractor captures both channel/column-based pattern...

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Bibliografski detalji

Glavni autori:	Mehmet Ali Gelen, Prabal Datta Barua, Irem Tasci, Gulay Tasci, Emrah Aydemir, Sengul Dogan, Turker Tuncer, U. R. Acharya
Format:	Artigo
Jezik:	Inglês
Izdano:	Nature Portfolio 2025-05-01
Serija:	Scientific Reports
Teme:	OTPat Explainable feature engineering Biomedical signal classification TkNN Directed lobish Cardioish
Online pristup:	https://doi.org/10.1038/s41598-025-00071-w
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