Nonparametric density-based clustering for cardiac arrhythmia analysis. Rodríguez-Sotelo, J., L., Peluffo-Ordoñez, D., Cuesta-Frau, D., & Castellanos-Domínguez, G. In Computers in Cardiology, 2009.
Nonparametric density-based clustering for cardiac arrhythmia analysis [link]Website  abstract   bibtex   2 downloads  
In this work, a nonsupervised algorithm for feature selection and a non-parametric density-based clustering algorithm are presented, whose density estimation is performed by Parzen's window approach; this algorithm solves the problem that individual components of the mixture should be Gaussian. The method is applied to a set of recordings from MIT/BIH's arrhythmia database with five groups of arrhythmias recommended by the AAMI. The heartbeats are characterized using prematurity indices, morphological and representation features, which are selected with the Q-α algorithm. The results are assessed by means supervised (Se, Sp, Sel) and nonsupervised indices for each arrhythmia. The proposed system presents comparable results than other unsupervised methods of literature.
@inproceedings{
 title = {Nonparametric density-based clustering for cardiac arrhythmia analysis},
 type = {inproceedings},
 year = {2009},
 websites = {https://ieeexplore.ieee.org/document/5445342/versions},
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 abstract = {In this work, a nonsupervised algorithm for feature selection and a non-parametric density-based clustering algorithm are presented, whose density estimation is performed by Parzen's window approach; this algorithm solves the problem that individual components of the mixture should be Gaussian. The method is applied to a set of recordings from MIT/BIH's arrhythmia database with five groups of arrhythmias recommended by the AAMI. The heartbeats are characterized using prematurity indices, morphological and representation features, which are selected with the Q-α algorithm. The results are assessed by means supervised (Se, Sp, Sel) and nonsupervised indices for each arrhythmia. The proposed system presents comparable results than other unsupervised methods of literature.},
 bibtype = {inproceedings},
 author = {Rodríguez-Sotelo, Jośe Luis and Peluffo-Ordoñez, D. and Cuesta-Frau, D. and Castellanos-Domínguez, G.},
 booktitle = {Computers in Cardiology}
}

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