Table 1

Techniques to characterize variability

Variability analysis
Description
Advantages
Limitations
Output variables

Time domain
Statistical calculations of consecutive intervals
Simple, easy to calculate; proven clinically useful; gross distinction of high and low frequency variations
Sensitive to artifact; requires stationarity; fails to discriminate distinct signals
SD, RMSDD Specific to HRV: SDANN, pNNx

Frequency distribution (plot number of observations falling in selected ranges or bins)
Visual representation of data; can fit to normal or log-normal distribution
Lacks widespread clinical application; arbitrary number of bins
Skewness (measures symmetry): positive (right tail) versus negative (left) Kurtosis (measures peakedness): flatter top (<0) versus peaked (>0)
Frequency domain
Frequency spectrum representation (spectral analysis)
Visual and quantitative representation of frequency contribution to waveform; useful to evaluate relationship to mechanisms; widespread HRV evaluation
Requires stationarity and periodicity for validity; sensitive to artifact; altered by posture, sleep, activity
Total power (area under curve) Specific to HRV: ULF (<0.003 Hz), VLF (0.003–0.04 Hz), LF (0.04–0.15 Hz), HF (0.15–0.4 Hz)
Time spectrum analysis
Scale invariant (fractal) analysis
Power law: log power versus log frequency
Ubiquitous biologic application; characterization of signal with single linear relationship; enables prognostication
Requires stationarity and periodicity; requires large datasets
Slope of power law Intercept of power law

DFA
Identifies intrinsic variations 2°system (versus external stimuli), does not require stationarity
Requires large datasets (>8000 patients)
Scaling exponent a1 (n < 11)
Scaling exponent a2 (n > 11)
a–ß filter
Entropy
Measures the degree of disorder (information or complexity)
Unique representation of data; requires fewest data points (100–900 patients)
Needs to be complemented by other techniques
ApEN SampEN Multi-scale entropy

ApEn, approximate entropy; DFA, detrended fluctuation analysis; HF, high frequency; HRV, heart rate variability; LF, low frequency; pNNx, proportion greater than x ms; RMSDD, root mean square of standard deviation; SampEn, sample entropy; SD, standard deviation; SDANN, standard deviation of 5 min averages; ULF, ultralow frequency; VLF, very low frequency.

Seely and Macklem Critical Care 2004 8:R367   doi:10.1186/cc2948