Risk evaluation of diabetes mellitus by relation of chaotic globals to HRV
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Data
2015-01-01
Autores
Souza, Naiara Maria de [UNESP]
Vanderlei, Luiz Carlos M. [UNESP]
Garner, David M.
Título da Revista
ISSN da Revista
Título de Volume
Editor
Wiley-Blackwell
Resumo
This study's aim is to analyze heart rate dynamics in subjects with diabetes by measures of heart rate variability (HRV). The correlation of chaotic global parameters in the two cohorts is able to assess the probability of cardiac failure and other dynamical diseases. Adults (46) were divided into two equal groups. The autonomic evaluation consisted of measuring HRV for 30 min in supine position in absence of any physical, sensory, or pharmacological stimuli. Chaotic global parameters are able to statistically determine which series of electrocardiograph interpeak intervals in short time-series are diabetic and which are not. The chaotic forward parameter that applies all three parameters is suggested to be the most appropriate and robust algorithm. This was decided after tests for normality; followed by one-way analysis of variance (ANOVA1); (P < 0.09) and Kruskal–Wallis technique (P < 0.03). Principal component analysis implied two components represent 99.8% of total variance. Therefore, diabetes is a disease which reduces the chaotic response and, as such may be termed a dynamical condition such as are cardiac arrest, asthma, and epilepsy.
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Palavras-chave
Diabetes, Nonlinear dynamics, Principal component analysis
Como citar
Complexity. Hoboken: Wiley-blackwell, v. 20, n. 3, p. 84-92, 2015.