Statistical modelling of the differences between successive R-R intervals.
Understanding the behaviour of R-R interval data and its successive differences is critical to the dynamics of cardiac control. Several time domain measures that quantify R-R interval variability have important clinical significance in terms of risk stratification and evaluating the effectiveness of treatment procedures. The present approach at examining the distributions of successive beat-to-beat differences of R-R interval data from different populations and under different conditions (baseline and reaction times) provides a valuable insight into their previously unexplored distributional properties. In particular, our analysis reveals that the successive differences have non-normal statistical distributions (a contradiction to the commonly used assumption of normality), and the absolute successive R-R interval differences approximately follows a Weibull distribution. As an illustration of the utility of this approach, we explore the statistical properties of the time domain measure: root mean square successive difference, study the association between the Weibull scale parameter estimate and respiratory sinus arrhythmia, and propose improvements in artifact detection algorithms.
Mandrekar
Sumithra J
SJ
The Ohio State University, Columbus, OH 43210, USA. mandrekar.sumithra@mayo.edu
Nagaraja
Haikady N
HN
Berntson
Gary G
GG
D000328:Adult; D000818:Animals; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D002648:Child; D004285:Dogs; D004562:Electrocardiography; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical