title: Cardiovascular autonomic function analysis using approximate entropy from 24-h heart rate variability and its frequency components in patients with type 2 diabetes.
abstract: OBJECTIVE
  The principal aim of the present study was to investigate the cardiovascular autonomic system status of diabetes patients using approximate entropy (ApEn) extracted from 24-h heart rate variability (HRV) and its frequency components.
  
  
  METHODS
  A total of 29 healthy controls and 63 type 2 diabetes patients were included. Participants' 24-h HRV signals were recorded, and decomposed and reconstructed into four frequency components: high, low, very low and ultra low. The total 24-h HRV and its four components were divided into 24 1-h segments. ApEn values were extracted and statistically analyzed. Four traditional HRV indices, namely standard deviation of the RR intervals, root mean square of successive differences, coefficient of variance of RR intervals and ratio of low to high power of HRV, were also calculated.
  
  
  RESULTS
  The low-frequency component contained the most abundant non-linear information, so was potentially most suitable for studying the cardiovascular system status with non-linear methods. ApEn values extracted from low- and high-frequency components of healthy controls were higher than those of diabetes patients. Except for root mean square of successive differences, standard deviation of the RR intervals, low to high power of HRV and coefficient of variance of RR intervals of healthy controls were all higher than those of diabetes patients.
  
  
  CONCLUSIONS
  The results showed that ApEn contained information on disorders of autonomic system function of diabetes patients as traditional HRV indices in time and frequency domains. ApEn and three traditional indices showed accordance to some degree. Non-linear information in subcomponents of HRV was shown, which is potentially more effective for distinguishing healthy individuals and diabetes patients than that extracted from the total HRV. Compared with diabetes patients, the cardiovascular system of healthy controls showed information of higher complexity, and better regulation function in response to changes of environment.
authors: School of Biomedical Engineering, Capital Medical University Beijing, China ; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University Beijing, China.
authors: Xia
authors: X
authors: Li
authors: School of Biomedical Engineering, Capital Medical University Beijing, China.
authors: Shuo
authors: S
authors: Yu
authors: School of Biomedical Engineering, Capital Medical University Beijing, China ; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University Beijing, China.
authors: Hui
authors: H
authors: Chen
authors: School of Biomedical Engineering, Capital Medical University Beijing, China.
authors: Cheng
authors: C
authors: Lu
authors: School of Biomedical Engineering, Capital Medical University Beijing, China ; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University Beijing, China.
authors: Kuan
authors: K
authors: Zhang
authors: Wangjing Hospital of China Academy of Traditional Chinese Medicine Beijing, China.
authors: Fangjie
authors: F
authors: Li
keywords: 24-h Heart rate variability; Approximate entropy; Cardiovascular autonomic function