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TopI. Introduction
The Poincaré plot (PP) is one of the important markers which analyses short as well as long term HR recordings. It is:
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A visual technique which can make use of pattern Recognition and a
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Quantitative one, which includes various parameters (called descriptors) which quantify the information contained in a Poincaré plot (Brennan, Palaniswami, & Kamen, 2001; Brennan, Palaniswami, & Kamen, 2002).
Developed by Henri Poincaré for analyzing complex systems, is used in physics, astronomy, meteorology, mathematical biology, geophysics and medical sciences (Ott, 1993). Medical sciences use it for quantifying the heart rate variability (HRV) and it stands as an effective measure of this marker (Brennan, Palaniswami, & Kamen, 2001; Brennan, Palaniswami, & Kamen, 2002; NASPE, 1996). It summarizes the entire recording, and simultaneously makes it possible to extract the information on short and long time behavior of the heart action. Being highly resistant, a reasonable Poincaré plot may be produced even from a recording containing a considerable amount of outliers and artifacts thus making it advantageous to the Discrete Fourier Transform (DFT) (usually realized by the Fast Fourier Transform (FFT) algorithm), where all outliers and artifacts must be noticed and dealt with. Concluding on information on sinus rhythm is important as many of the conclusions drawn from HRV analysis refer to the sinus rhythm (NASPE, 1996).
TopIi. Heart Rate Variability
Heart beats are caused by electrical depolarization of the heart muscle (Eckberg, 1997; Eckberg, 2003; Parati, Saul, & Castiglioni, n.d.; Mrowka, Persson, Theres, & Patzak, 2000). Electrical depolarization of the different parts of heart can be observed on an electrocardiogram (ECG) (Figure 1).
Figure 1. A strip of ECG presenting heart’s electrical activity recorded in a healthy person
The momentary heart rate and the duration of the RR interval is a consequence of constant interaction between the intrinsic activity of the sinus node and the influence of the autonomic nervous system, various substances circulating in the blood and present in the heart tissues (Eckberg, 2003; Parati, Saul, & Castiglioni, n.d.). Breathing appears to be the most important factor modulating heart rate (Eckberg, 2003; Parati, Saul, & Castiglioni, n.d.; Guzik et al., 2005). The changes in blood pressure modulated by baroreflex are another example of a separate system regulating the heart rate. The control of heart rate is modulated by both sympathetic and parasympathetic branches of autonomic nervous system as well as many other autonomic reflexes (e.g., chemoreflexes) (Parati, Saul, & Castiglioni, n.d.; Guzik et al., 2005; Guzik et al., 2005) All these systems and reflexes are responsible for changing of the duration of RR interval from one beat to another and this phenomenon is called heart rate variability (HRV) [13, 15, 7, 8]. It is accepted that the higher HRV, the better prognosis in survivors of myocardial infarction or patients with heart failure. HRV is reduced in patients with diabetes and autonomic dysfunction. Frequency–domain analyses contributed to the understanding of the autonomic background of RR interval fluctuations in the heart rate record (Seely & Macklem, 2004). Frequency-domain or spectral analysis of time series of RR intervals is performed with Discrete Fourier Transformation (usually by FFT) or autoregressive models. Derived from spectral HRV analysis, the total power represents total HRV, the power of high frequency (HF) corresponds to parasympathetic activity while the power of low frequency (LF) depends on both sympathetic and parasympathetic activity and their balance (Seely & Macklem, 2004).