Clinical Applications of Heart Rate Variability in the Triage and Assessment of Traumatically Injured Patients

Table 3

Definitions of entropy metrics of heart rate variability.

Variable	Abbreviation	Description	Interpretation
Approximate entropy	ApEn	Measures the amount of irregularity in the RRI signal [40, 41]	Lower value reflects less complex signal
Sample entropy	SampEn
Multiscale entropy	MSE	The sum of sample entropies [37]
Similarity of distributions	SOD	The probability of similar RRI signal amplitude distributions as a function of time [33]	Higher SOD reflects more similarity and less complex regulation
Point correlation dimension	PD2i	Measures time-dependent changes in the degrees of freedom of a data set [33]	Lower value signifies loss of regulatory complexity
Fractal dimension by dispersion analysis	FDDA	Determines the fractal organization of the signal; measures self-similarity in the signal structure [41]	Lower value implies lower complexity of signal regulation
Fractal dimension by curve lengths	FDCL
Detrended fluctuations analysis	DFA	Determines fractal-like correlation properties and uncovers short- and long-range correlations within the signal [42]	Distinguishes between fluctuations generated by complex systems and those arising from external stimuli
Signal stationarity	StatAv	Assesses whether the mean and SD of the signal change during time in each data set [8]	Lower value reflects a more stationary signal
Symbol dynamics entropy	SymDyn	Measures the probability of certain patterns within the RRI time series [33]	Lower value implies a more predictable signal with less complex regulation
Percentage of forbidden words	FW
Symbol distribution entropy	DisnEn