The AcqKnowledge software includes a fully automated Heart Rate Variability analysis tool. The algorithm conforms to the frequency domain algorithm guidelines as published by the European Heart Journal. HRV processing in AcqKnowledge consists of three stages.
The RR intervals are extracted for the ECG signal.
A modified Pan-Tompkins QRS detector is used.
The RR intervals are re-sampled to a continuous sampling rate in order to extract frequency information.
Cubic-spline interpolation is used to generate this continuous time-domain representation of the RR intervals.
The frequency information is extracted from the RR intervals and analyzed to produce standard ratios. Power sums are reported in units of sec2/Hz. A Welch periodogram is used to generate the Power Spectral Density (equivalent to Transform > Power Spectral Density).
Beat detection parameters—Configure the behavior of the QRS detector. The standard settings should function on a wide range of data sets, but you can adjust the thresholds for your particular data set. Use the tachogram output to examine the output of the QRS detector.
Note: The BioHarness is not recommended for heart rate variability studies because the sample rate used to record the ECG waveform is at the very low end of the optimal range for HRV studies.
