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Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS(2)
2015 20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015 - Conference Proceedings(1)
2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016(1)
Progress in Biomedical Optics and Imaging - Proceedings of SPIE(1)
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Fisiología humana(5)
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scopus(5)
Classification of metabolic syndrome subjects and marathon runners with the k-means algorithm using heart rate variability features
Conference ObjectAbstract: In this paper, we have applied the k-means clustering algorithm to classify three study groups (peopPalabras claves:Autores:Altuve M., Perpinan G., Sara Wong De Balzan, Severeyn E.Fuentes:rraaescopusComparing glucose and insulin data from the two-hour oral glucose tolerance test in metabolic syndrome subjects and marathon runners
Conference ObjectAbstract: Glucose is the main energy source of the body's cells and is essential for normal metabolism. Two paPalabras claves:Autores:Altuve M., Perpinan G., Sara Wong De Balzan, Severeyn E.Fuentes:rraaescopusAnthropometric measurements for assessing insulin sensitivity on patients with metabolic syndrome, sedentaries and marathoners
Conference ObjectAbstract: The diagnosis of low insulin sensitivity is commonly done through the HOMA-IR index, in which fastinPalabras claves:Autores:Altuve M., Herrera H., Sara Wong De Balzan, Severeyn E.Fuentes:rraaescopusExtracting stationary segments from non-stationary synthetic and cardiac signals
Conference ObjectAbstract: Physiological signals are commonly the result of complex interactions between systems and organs, thPalabras claves:Diabetic cardiovascular autonomic neuropathy, Heart Rate Variability, Non-stationary time series, RR interval, Scale invariance, Statistical Analysis, STRESS TEST, synthetic data generationAutores:Altuve M., Ledezma C.A., Perpinan G., Rodriguez M.G., Sara Wong De BalzanFuentes:rraaescopusUnsupervised subjects classification using insulin and glucose data for insulin resistance assessment
Conference ObjectAbstract: In this paper, the κ-means clustering algorithm is employed to perform an unsupervised classificatioPalabras claves:Autores:Altuve M., Sara Wong De Balzan, Severeyn E.Fuentes:rraaescopus