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Table 2 The list of features extracted from HRV

From: Sleep stage classification using extreme learning machine and particle swarm optimization for healthcare big data

No.

Name of feature

Method of extraction

Explanation

1

AVNN

Time domain

AVNN is mean of all normal sinus to normal sinus of NN intervals.

\(AVNN = \frac{1}{N}\mathop \sum \limits_{j = 1}^{N} RR_{j}\) where j is interval index and N is number of total intervals

2

SDNN

Time domain

SDNN is the standard deviation of NN intervals

\(SDNN\;\text{ = }\;\sqrt {\frac{1}{{N\;\text{ - }\;1}}\;\sum\limits_{{j\;\text{ = }\;1}}^{N} {\left( {RR_{j} \text{ - }\;\overline{{\text{RR}}} } \right)^{2} } }\)

3

RMSSD

Time domain

Root Mean Square of the Successive Differences (RMSSD)

\(RMSSD = \sqrt {\frac{1}{N - 1}\mathop \sum \limits_{j = 1}^{N - 1} \left( {RR_{j + 1} - RR_{j} } \right)^{2} }\)

4

SDSD

Time domain

The standard deviation of the successive difference between adjacent R-R intervals

5

NN50

Time domain

The number of pairs of adjacent NN intervals differing by more than 50 ms

\(Number of \left( {RR_{j + 1} - RR_{j} } \right) > 50\)

6

pNN50

Time domain

Percentage of adjacent NN intervals differing by more than 50 ms

\(pNN50 = \frac{NN50}{N - 1} \times 100\)

7

HRV Triangular Index

Geometrical

(The total number of RR intervals)/(the height of histogram of all RR intervals with 7.8125 ms bin)

8

SD1

Poincare

\(SD1^{2} = \frac{1}{2}SDSD^{2}\) where SD1 = the standard deviation of perpendicular points to the line-of-identity

9

SD2

Poincare

\(SD2^{2} = 2SDNN^{2} - \frac{1}{2}SDSD^{2}\) where SD2 = the standard deviation of parallel points along the line-of-identity

10

SD1SD2 Ratio

Poincare

\(SD1 SD2 Ratio = \frac{SD1}{SD2}\)

11

S

Poincare

\(S = \pi \times {\text{SD}}1 \times {\text{SD}}2\)

12

TP

Frequency domain

The total power (TP) of the HRV

13

VLF

Frequency domain

Very low frequency (VLF) is defined as the total power (TP) ranging from 0‒0.04 Hz

14

LF

Frequency domain

Low frequency is defined as the total power (TP) ranging from 0.04‒0.15 Hz

15

HF

Frequency domain

High frequency is defined as the total power (TP) ranging from 0.15‒0.4 Hz

16

LFHF Ratio

Frequency domain

The ratio of LF to HF indicates the sympathovagal balance.

17

LFnorm

Frequency domain

\(LFnorm = \frac{LF}{TP - VLF}\)

18

HFnorm

Frequency domain

\(HFnorm = \frac{HF}{TP - VLF}\)