title: Complexity analysis of beat-to-beat skin-surface laser-Doppler signals in diabetic subjects.
abstract: BACKGROUND
  This study performed skin-surface laser-Doppler flowmetry (LDF) measurements with the aim of verifying if complexity analysis applied to the beat-to-beat LDF waveform index can be used to discriminate diabetic, prediabetic, and normoglycemic subjects.
  
  
  METHODS
  Sixty-six subjects were assigned to three age-matched groups according to the results of oral glucose tolerance tests. Beat-to-beat analysis was performed on the pulsatile LDF waveform to obtain the pulse-to-mean ratio (AD) and pulse width (PW), and then approximate-entropy (ApEn) values for their 20-minute index sequences were calculated to evaluate the signal complexity.
  
  
  RESULTS
  AD and PW did not differ significantly among the three study groups. ApEn values of AD and PW were significantly larger and marginally larger, respectively, in the diabetic group than in the prediabetic and normoglycemic groups.
  
  
  CONCLUSIONS
  These results indicate the presence of significant differences in ApEn indexes among diabetic, prediabetic, and normoglycemic subjects. The presence of increased complexity in the LDF index sequence may be partly attributed to the adaptability of the microcirculatory regulatory activities or the impairment of the homeostasis mechanism of microcirculatory-blood-flow perfusion. The present findings may be pertinent to the early detection of the diabetes-induced impairment of this perfusion.
authors.affiliation: Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. Electronic address: hhsiu@mail.ntust.edu.tw.
authors.forename: Hsin
authors.initials: H
authors.lastname: Hsiu
authors.affiliation: Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taipei, Taiwan.
authors.forename: Chia Liang
authors.initials: CL
authors.lastname: Hsu
authors.affiliation: Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taipei, Taiwan; Department of Emergency Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
authors.forename: Hsiao-Feng
authors.initials: HF
authors.lastname: Hu
authors.affiliation: Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
authors.forename: Fone-Ching
authors.initials: FC
authors.lastname: Hsiao
authors.affiliation: Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
authors.forename: Shu-Han
authors.initials: SH
authors.lastname: Yang
mesh_terms: D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D016022:Case-Control Studies; D003925:Diabetic Angiopathies / Q000097:blood / Q000175:diagnosis / Q000503:physiopathology*; D042241:Early Diagnosis; D004562:Electrocardiography; D005951:Glucose Tolerance Test; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D017078:Laser-Doppler Flowmetry; D008833:Microcirculation; D011236:Prediabetic State / Q000097:blood / Q000175:diagnosis / Q000503:physiopathology*; D011237:Predictive Value of Tests; D012039:Regional Blood Flow; D012815:Signal Processing, Computer-Assisted; D012867:Skin / Q000098:blood supply*; D013997:Time Factors
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human