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초록
This study presents a novel approach called Multi-slice Nested Recurrence Plot (MsNRP) for person iden-tification using noisy bio-signals. Prior studies in biometrics have predominantly relied on ideal datasets of 5-10 min, which introduces uncertainty in accuracy when dealing with noisy bio-signals. The proposed MsNRP method captures features from one and multiple cycles without the need for preprocessing, making it well-suited for photoplethysmograms(PPG) and electrocardiograms(ECG). By overcoming the limitations of traditional recurrence plots(RP), MsNRP demonstrates robustness to noisy bio-signal datasets, thus offering a reliable solution for identification in practical scenarios. We demonstrate the experiments of MsNRP on both 5-10 min datasets, similar to previous related work and day-long datasets, measured in daily life emphasizing its robustness in handling noisy data.
키워드
- 제목
- Multi-slice Nested Recurrence Plot (MsNRP): A robust approach for person identification using daily ECG or PPG signals
- 저자
- Jeon, YeongJun; Kang, Soon Ju
- 발행일
- 2023-11
- 유형
- Article
- 권
- 126
- 언어
- ENG
- 출판사
- PERGAMON-ELSEVIER SCIENCE LTD
- 발행국가
- 영국
- ISSN
- E 1873-6769
P 0952-1976