Cargando…
Convolutional Neural Network for Individual Identification Using Phase Space Reconstruction of Electrocardiogram
Electrocardiogram (ECG) biometric provides an authentication to identify an individual on the basis of specific cardiac potential measured from a living body. Convolutional neural networks (CNN) outperform traditional ECG biometrics because convolutions can produce discernible features from ECG thro...
Autores principales: | Chan, Hsiao-Lung, Chang, Hung-Wei, Hsu, Wen-Yen, Huang, Po-Jung, Fang, Shih-Chin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10056305/ https://www.ncbi.nlm.nih.gov/pubmed/36991875 http://dx.doi.org/10.3390/s23063164 |
Ejemplares similares
-
High-Dimensional Phase Space Reconstruction with a Convolutional Neural Network for Structural Health Monitoring
por: Chen, Yen-Lin, et al.
Publicado: (2021) -
Robustness of convolutional neural networks to physiological electrocardiogram noise
por: Venton, J., et al.
Publicado: (2021) -
Identification of supraventricular tachycardia mechanisms with surface electrocardiograms using a convolutional neural network
por: Higuchi, Satoshi, et al.
Publicado: (2023) -
Electrocardiogram Classification Based on Faster Regions with Convolutional Neural Network
por: Ji, Yinsheng, et al.
Publicado: (2019) -
Convolutional neural network optimized by differential evolution for electrocardiogram classification
por: Chen, Shan Wei, et al.
Publicado: (2023)