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Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 231762, 7 pages
http://dx.doi.org/10.1155/2013/231762
Research Article

Multiscale Cross-Approximate Entropy Analysis as a Measurement of Complexity between ECG R-R Interval and PPG Pulse Amplitude Series among the Normal and Diabetic Subjects

1Department of Electrical Engineering, National Dong Hwa University, Hualien 97401, Taiwan
2Department of Neurology, Buddhist Tzu Chi General Hospital and Buddhist Tzu Chi University, No. 707, Section 3, Chung-Yang Road, Hualien 97074, Taiwan

Received 21 June 2013; Revised 6 August 2013; Accepted 14 August 2013

Academic Editor: Kevin Ward

Copyright © 2013 Hsien-Tsai Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Physiological signals often show complex fluctuation (CF) under the dual influence of temporal and spatial scales, and CF can be used to assess the health of physiologic systems in the human body. This study applied multiscale cross-approximate entropy (MC-ApEn) to quantify the complex fluctuation between R-R intervals series and photoplethysmography amplitude series. All subjects were then divided into the following two groups: healthy upper middle-aged subjects (Group 1, age range: 41–80 years, ) and upper middle-aged subjects with type 2 diabetes (Group 2, age range: 41–80 years, ). There are significant differences of heart rate variability, LHR, between Groups 1 and 2 ( versus , ). Results demonstrated differences in sum of large scale MC-ApEn (MC-) ( versus , ). This parameter has a good agreement with pulse-pulse interval and pulse amplitude ratio (PAR), a simplified assessment for baroreflex activity. In conclusion, this study employed the MC-ApEn method, integrating multiple temporal and spatial scales, to quantify the complex interaction between the two physical signals. The MC- parameter could accurately reflect disease process in diabetics and might be another way for assessing the autonomic nerve function.