Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department

Liu, Nan; Chee, Marcel Lucas; Koh, Zhi Xiong; Leow, Su Li; Ho, Andrew Fu Wah; Guo, Dagang; Ong, Marcus Eng Hock

doi:10.1186/s12874-021-01265-2

Table 1 List of traditional heart rate variability (HRV) and novel heart rate n-variability (HRnV) parameters used in this study. HRnV is a new representation of beat-to-beat variation in ECGs and parameter “n” controls the formation of new RR-intervals that are used for parameter calculation. Details of HRnV definition can be found in [28]

From: Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department

HRV	HR₂V	HR₂V₁	HR₃V	HR₃V₁	HR₃V₂
Mean NN	HR₂V Mean NN	HR₂V₁ Mean NN	HR₃V Mean NN	HR₃V₁ Mean NN	HR₃V₂ Mean NN
SDNN	HR₂V SDNN	HR₂V₁ SDNN	HR₃V SDNN	HR₃V₁ SDNN	HR₃V₂ SDNN
RMSSD	HR₂V RMSSD	HR₂V₁ RMSSD	HR₃V RMSSD	HR₃V₁ RMSSD	HR₃V₂ RMSSD
Skewness	HR₂V Skewness	HR₂V₁ Skewness	HR₃V Skewness	HR₃V₁ Skewness	HR₃V₂ Skewness
Kurtosis	HR₂V Kurtosis	HR₂V₁ Kurtosis	HR₃V Kurtosis	HR₃V₁ Kurtosis	HR₃V₂ Kurtosis
Triangular index	HR₂V Triangular index	HR₂V₁ Triangular index	HR₃V Triangular index	HR₃V₁ Triangular index	HR₃V₂ Triangular index
NN50	HR₂V NN50	HR₂V₁ NN50	HR₃V NN50	HR₃V₁ NN50	HR₃V₂ NN50
pNN50	HR₂V pNN50	HR₂V₁ pNN50	HR₃V pNN50	HR₃V₁ pNN50	HR₃V₂ pNN50
–	HR₂V NN50n	HR₂V₁ NN50n	HR₃V NN50n	HR₃V₁ NN50n	HR₃V₂ NN50n
–	HR₂V pNN50n	HR₂V₁ pNN50n	HR₃V pNN50n	HR₃V₁ pNN50n	HR₃V₂ pNN50n
Total power^a	HR₂V Total power	HR₂V₁ Total power	HR₃V Total power	HR₃V₁ Total power	HR₃V₂ Total power
VLF power	HR₂V VLF power	HR₂V₁ VLF power	HR₃V VLF power	HR₃V₁ VLF power	HR₃V₂ VLF power
LF power	HR₂V LF power	HR₂V₁ LF power	HR₃V LF power	HR₃V₁ LF power	HR₃V₂ LF power
HF power	HR₂V HF power	HR₂V₁ HF power	HR₃V HF power	HR₃V₁ HF power	HR₃V₂ HF power
LF power norm	HR₂V LF power norm	HR₂V₁ LF power norm	HR₃V LF power norm	HR₃V₁ LF power norm	HR₃V₂ LF power norm
HF power norm	HR₂V HF power norm	HR₂V₁ HF power norm	HR₃V HF power norm	HR₃V₁ HF power norm	HR₃V₂ HF power norm
LF/HF	HR₂V LF/HF	HR₂V₁ LF/HF	HR₃V LF/HF	HR₃V₁ LF/HF	HR₃V₂ LF/HF
Poincaré SD1	HR₂V Poincaré SD1	HR₂V₁ Poincaré SD1	HR₃V Poincaré SD1	HR₃V₁ Poincaré SD1	HR₃V₂ Poincaré SD1
Poincaré SD2	HR₂V Poincaré SD2	HR₂V₁ Poincaré SD2	HR₃V Poincaré SD2	HR₃V₁ Poincaré SD2	HR₃V₂ Poincaré SD2
Poincaré SD1/SD2 ratio	HR₂V Poincaré SD1/SD2	HR₂V₁ Poincaré SD1/SD2	HR₃V Poincaré SD1/SD2	HR₃V₁ Poincaré SD1/SD2	HR₃V₂ Poincaré SD1/SD2
SampEn	HR₂V SampEn	HR₂V₁ SampEn	HR₃V SampEn	HR₃V₁ SampEn	HR₃V₂ SampEn
ApEn	HR₂V ApEn	HR₂V₁ ApEn	HR₃V ApEn	HR₃V₁ ApEn	HR₃V₂ ApEn
DFA, α1	HR₂V DFA, α1	HR₂V₁ DFA, α1	HR₃V DFA, α1	HR₃V₁ DFA, α1	HR₃V₂ DFA, α1
DFA, α2	HR₂V DFA, α2	HR₂V₁ DFA, α2	HR₃V DFA, α2	HR₃V₁ DFA, α2	HR₃V₂ DFA, α2

Mean NN average of R-R intervals, SDNN standard deviation of R-R intervals, RMSSD square root of the mean squared differences between R-R intervals, NN50 the number of times that the absolute difference between 2 successive R-R intervals exceeds 50 ms pNN50, NN50 divided by the total number of R-R intervals, NN50n the number of times that the absolute difference between 2 successive RR_nI/RR_nI_m sequences exceeds 50 × n ms, pNN50n NN50n divided by the total number of RR_nI/RR_nI_m sequences, VLF very low frequency, LF low frequency, HF high frequency, SD standard deviation, SampEn sample entropy, ApEn approximate entropy, DFA detrended fluctuation analysis
^aIn frequency domain analysis, the power of spectral components is the area below the relevant frequencies presented in absolute units (square milliseconds)

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ISSN: 1471-2288

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