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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| 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: | |
| Online Access: | https://doi.org/10.1038/s41598-025-00071-w |
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