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

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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Bibliographic Details
Main Authors: Mehmet Ali Gelen, Prabal Datta Barua, Irem Tasci, Gulay Tasci, Emrah Aydemir, Sengul Dogan, Turker Tuncer, U. R. Acharya
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
OTPat
Explainable feature engineering
Biomedical signal classification
TkNN
Directed lobish
Cardioish
Online Access:https://doi.org/10.1038/s41598-025-00071-w
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