%0 Journal Article
%T SDNN/RMSSD as a Surrogate for LF/HF: A Revised Investigation
%A Hui-Min Wang
%A Sheng-Chieh Huang
%J Modelling and Simulation in Engineering
%D 2012
%I Hindawi Publishing Corporation
%R 10.1155/2012/931943
%X Thousands of papers involved in heart rate variability (HRV). However, little was known about one important measure of HRV, the root mean square of successive heartbeat interval differences (RMSSDs). Another fundamental measure SDNN indicates standard deviation of normal to normal R-R intervals, where R is the peak of a QRS complex (heartbeat). Compared with SDNN, RMSSD is a short-term variation of heart rate. Through a time-frequency transformation, the ratio of low- and high-frequency power LF/HF represents the sympatho-vagal balance of the autonomic nervous system (ANS). Some research claimed that SDNN/RMSSD was a good surrogate for LF/HF. However, only two special cases supported this hypothesis in the literature survey. The first happened in resting supine state and the other was a group of prefrontal cortex patients. Both of their Pearson correlation coefficients reached 0.90, a reasonable criterion. In our study, a 6-week experiment was performed with 32 healthy young Asian males. The Pearson correlation coefficients had a normal distribution with average values smaller than 0.6 for 3 and 5-minute epochs, respectively. Our findings suggest this surrogate aspect could remain as a hypothesis. 1. Introduction RMSSD, the root mean square differences of successive R-R (heartbeat) intervals, is a significant indicator for both atrial fibrillation (AF) and sudden unexplained death in epilepsy (SUDEP) [1, 2]. Beyond RMSSD, some other essential variables of heart rate variability (HRV) measures are SDNN, LF and HF. SDNN is the standard deviation of normal to normal R-R intervals. LF and HF represent power in low- and high-frequency ranges [3]. Previous research suggested that SDNN/RMSSD was a good surrogate of LF/HF for healthy subjects [4, 5]. Whether this statement is affirmative would be revised by analysis of cardiac measurements in this paper. Measurements of HRV include time domain, frequency domain methods, and so on. They are noninvasive, as the tools to recognize the relationship between the autonomic nervous system (ANS) and cardiovascular mortality [3]. Figure 1 shows a standard routine of electrocardiogram (ECG) signal processing [6]. Detection of heartbeats (QRS complexes) is the first step, where R is the peak of the complex. The time domain analysis (SDNN, RMSSD) reports the activity of the cardiac system. The frequency domain analysis (LF, HF) reflects sympathovagal balance of the ANS. These HRV variables can be calculated easily through a superlative software package [7]. As time went by, HRV yielded rich fruits in various applications
%U http://www.hindawi.com/journals/mse/2012/931943/