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Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects.
Xiao, Ming-Xia; Wei, Hai-Cheng; Xu, Ya-Jie; Wu, Hsien-Tsai; Sun, Cheuk-Kwan.
Afiliación
  • Xiao MX; School of Electrical and Information Engineering, North Minzu University, No. 204 North-Wenchang St., Xixia District, Yinchuan 750021, China.
  • Wei HC; School of Computer and Information, Hefei University of Technology, No. 193, Tunxi Rd., Hefei 230009, China.
  • Xu YJ; School of Electrical and Information Engineering, North Minzu University, No. 204 North-Wenchang St., Xixia District, Yinchuan 750021, China.
  • Wu HT; School of Electrical and Information Engineering, North Minzu University, No. 204 North-Wenchang St., Xixia District, Yinchuan 750021, China.
  • Sun CK; Department of Electrical Engineering, National Dong Hwa University, No. 1, Sec. 2, Da Hsueh Rd., Shoufeng, Hualien 97401, Taiwan.
Entropy (Basel) ; 20(7)2018 Jun 27.
Article en En | MEDLINE | ID: mdl-33265587
ABSTRACT
The present study aimed at testing the hypothesis that application of multiscale cross-approximate entropy (MCAE) analysis in the study of nonlinear coupling behavior of two synchronized time series of different natures [i.e., R-R interval (RRI) and crest time (CT, the time interval from foot to peakof a pulse wave)] could yield information on complexity related to diabetes-associated vascular changes. Signals of a single waveform parameter (i.e., CT) from photoplethysmography and RRI from electrocardiogram were simultaneously acquired within a period of one thousand cardiac cycles for the computation of different multiscale entropy indices from healthy young adults (n = 22) (Group 1), upper-middle aged non-diabetic subjects (n = 34) (Group 2) and diabetic patients (n = 34) (Group 3). The demographic (i.e., age), anthropometric (i.e., body height, body weight, waist circumference, body-mass index), hemodynamic (i.e., systolic and diastolic blood pressures), and serum biochemical (i.e., high- and low-density lipoprotein cholesterol, total cholesterol, and triglyceride) parameters were compared with different multiscale entropy indices including small- and large-scale multiscale entropy indices for CT and RRI [MEISS(CT), MEILS(CT), MEISS(RRI), MEILS(RRI), respectively] as well as small- and large-scale multiscale cross-approximate entropy indices [MCEISS, MCEILS, respectively]. The results demonstrated that both MEILS(RRI) and MCEILS significantly differentiated between Group 2 and Group 3 (all p < 0.017). Multivariate linear regression analysis showed significant associations of MEILS(RRI) and MCEILS(RRI,CT) with age and glycated hemoglobin level (all p < 0.017). The findings highlight the successful application of a novel multiscale cross-approximate entropy index in non-invasively identifying diabetes-associated subtle changes in vascular functional integrity, which is of clinical importance in preventive medicine.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Entropy (Basel) Año: 2018 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Entropy (Basel) Año: 2018 Tipo del documento: Article País de afiliación: China