Heart Rate Turbulence (HRT) is a powerful risk stratification criterion in patients with cardiac disorders. Several physiological factors affect HRT, mainly, heart rate (HR), and coupling interval (CI). However, classical HRT assessment uses an average of the available individual tachograms that can blur relevant physiological relationships and it does not take into account their impact on HRT. We hypothesized that quantifying the impact of CI and HR on individual tachograms, by using robust signal processing techniques, will allow to compute local HRT measurements, yielding a more complete and meaningful HRT characterization. We studied 11 patients who were referred for electrophysiological studies. Sequences of single ventricular extrastimuli were delivered with controlled HR and adjusted CI. Turbulence Slope and Turbulence Onset were computed in denoised individual tachograms, and their effect was studied. Results showed that HRT decreased when increasing the HR and the CI. Our denoising approach allowed, for the first time, to clearly quantify these results in individual patients and even in isolated tachograms. The effect of HR and CI on the HRT that can be taken into account by denoising isolated tachograms, yielding a more accurate physiological description of HRT.
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