Compression based entropy estimation of heart rate variability on multiple time scales

• Published in: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2013; pp. 5037 - 5040
• Main Authors: Baumert, Mathias, Voss, Andreas, Javorka, Michal
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2013
• Subjects: Adult; Aged; Aged, 80 and over; Algorithms; Complexity theory; Data Compression; Entropy; Heart Rate - physiology; Heart rate variability; Humans; Middle Aged; Physiology; Time Factors; Time series analysis; Young Adult
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/EMBC.2013.6610680

Heart rate fluctuates beat by beat in a complex manner. The aim of this study was to develop a framework for entropy assessment of heart rate fluctuations on multiple time scales. We employed the Lempel-Ziv algorithm for lossless data compression to investigate the compressibility of RR interval time series on different time scales, using a coarse-graining procedure. We estimated the entropy of RR interval time series of 20 young and 20 old subjects and also investigated the compressibility of randomly shuffled surrogate RR time series. The original RR time series displayed significantly smaller compression entropy values than randomized RR interval data. The RR interval time series of older subjects showed significantly different entropy characteristics over multiple time scales than those of younger subjects. In conclusion, data compression may be useful approach for multiscale entropy assessment of heart rate variability.