From Heart Rate Variability to Autonomic Nervous System - Poincaré plot vs. Spectral Analysis
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
International Conference on Computer Aided Systems Theory (EUROCAST 2017)
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
The heart rate variability (HRV) derived from the electrocardiogram (ECG) is the sequence of successive R-peaks R[n] of adjacent heart cycles. This sequence contains fundamental information about the condition of the individual heart and the cardiovascular regulatory mechanisms of the autonomic nervous system (ANS). One way to evaluate the two branches of the ANS has been shown in a previous publication. There, spectral analysis of the HRV by a continuous wavelet transform (CWT) with a non-analytical Morlet wavelet has confirmed the presence of an autonomic dysfunction in demented patients. Parasympathetic tone can be found in the HRV?s HF frequency band (0.15?0.4Hz) whereas frequencies from 0.04?0.15Hz (LF frequency band) contain a mixture of parasympathetic and sympathetic activity. Due to edge effects, the wavelet transform requires long examination times often unfeasible for demented patients. A common method of visualization of HRV data is the Poincare plot, a scatterplot showing R[n + 1] over R[n], which is used to categorize data into functional classes, indicating the integrity of the heart and possible heart failures. The Poincare plot, although frequently used for clinical purposes, only provides little quantitative measures. We show in this work how to derive measures from the Poincare plot proving AND diagnostics for demented patients with comparable reliability as the wavelet transformation, but requiring lower examination times.