0. Preprocessing of RR intervals (RRIntervalPreprocess.m)

This function preprocesses RR interval data in preparation for running HRV analyses. 
Noise and non-normal beats are removed from the RR interval data and replaced with
interpolated data using a interpolation method of choice.

Output         ||                               ||
================================================================================
NNinterp3      ||     interp1.m                 ||  After noise and non-normal beats 
tinterp3       ||     interp1.m                 ||  are removed data are interpoleted 
flagged_beats  ||                               ||  using "interp1.m" Matlab fucntion

_________________________________________________________________________________________________________________________________________________________

1. Time Domain Metrics   ( EvalTimeDomainHRVstats)

HRV Metric      ||     Function used            ||      Note
                ||    for computation           ||  
==================================================================================
NNmean          ||     mean.m                   || (Matlab function)           
NNmedian        ||     median.m                 || (Matlab function)           
NNmode          ||     mode.m                   || (Matlab function)           
NNvariance      ||     var.m                    || (Matlab function)           
NNskew          ||     skewness.m               || (Matlab function)           
NNkurt          ||     kurtosis.m               || (Matlab function)           
NNiqr           ||     iqr.m                    || (Matlab function)          
SDNN            ||     std.m                    || (Matlab function)         --  Standard deviation of NN intervals         
RMSSD           ||     runrmssd.m               || Adapted from Kaplan Tools --  Square root of the mean of the sum of the squares of the differences 
pnn50           ||     pnna.m                   || Adapted from Kaplan Tools --  Finds the fraction of consecutive beats that differ by more 50 msec
btsdet          ||     length.m                 || (Matlab function)           

_________________________________________________________________________________________________________________________________________________________

2. Frequency Domain Metrics  ( EvalFrequencyDomainHRVstats.m)

HRV Metric      ||     Function used            ||      Note
                ||    for computation           ||  
==================================================================================
ulf             ||    CalcLfHfParams.m          || need Power Spectral Density (PSD) as input, it is computed 
vlf             ||    CalcLfHfParams.m          || using "pwelch.m" or "pburg.m "Matlab function *
lf              ||    CalcLfHfParams.m          || 
hf              ||    CalcLfHfParams.m          || or Lomb-Scargle normalized periodogram using 
lfhf            ||    CalcLfHfParams.m          || provided CalcLomb.m function which is quivalent
ttlpwr          ||    CalcLfHfParams.m          || to Matlab plomb.m
                                                ||
                                                || or double sided spectrum using FFT

 

_________________________________________________________________________________________________________________________________________________________


4. Acceleration and Deceleration Metrics (prsa.m)


HRV Metric      ||     Function used            ||      Note
                ||    for computation           ||  
==================================================================================
ac_results      ||    prsa.m                    || This function was originall written by 
dc_results      ||    prsa.m                    || L.Campana and G.D.Clifford modyfied by 
                                                   A.Vest to be used in HRV toolbox


5. Calculates SDANN and SDNNindex (ClalcSDANN.m)

HRV Metric      ||     Function used            ||      Note
                ||    for computation           ||  
==================================================================================
SDANN           ||    std.m                     || Standard deviation of the averages of values
SDNNI           ||    mean.m                    || Mean of the standard deviations of all values

