WHAT IS HEART RATE VARIABILITY (HRV) ANALYSIS?

In the last few years HRV acquired an extreme popularity in almost all branches of contemporary medicine, including in the area of prevention. One of the creators of this new trend is Prof. Dr. Svetoslav Danev, who proved that the unfavorable changes in HRV could be used as a predictor of wide range of life-threatening diseases, including carciomatosis. This was determined in the course of a long-year cohort research and monitoring.

Since HRV reflects most directly the balance in the two branches of the vegetative nervous system – sympathicus and parasympathicus (vagus), this triggered the creation of a new important bio-constant – the so called vegetative equilibrium. It has a wide application not only in the prevention, but also in other branches of medicine.

From a mathematical perspective, HRV reflects the regularity of the heart beat activity - increased regularity corresponds to decreased heart rate variability, and vice versa. The heart rate variability is derived from the difference in time intervals elapsed between two consecutive heartbeats, called cardiointervals (R-R intervals) and measured in milliseconds (ms). The cardiointervals are received from the ECG signal, as it is demonstrated on the figure bellow.

ECG is electrocardiogram, the QRS complexes correspond to heartbeats, and R-R 1 and R-R 2 are cardiointervals.

The increased sympathicus activity (tone) results in a decreased HRV, and vice versa – the increased parasympathicus activity increases the HRV.

HRV presents an opportunity for mathematical calculation of the following parameters:

·    time-based parameters – short-term and long-term standard deviations of cardiointervals, histogram, scatterogram, etc.

·    frequency-based parameters – general spectral power, its percentage distribution in the different spectral ranges, short/long spectral waves, correlation, etc.

·    parameters based on spectral coincidences (amplitude) – spectral coincidences between HRV and Plethismographic spectrum. The coincidence provides information for the psychosomatic capacity for adaptation to stress. The increased occurrence of coincidences reflects increased adaptation capacity, and vice versa.

·    ECG-based parameters – a number of ECG events which can be potential ventricular or supraventricular extrasystoles (premature heartbeats), certain pathological deviations of the QRS complex (the QRS complexes correspond to heartbeats), T-waves, etc.

Statistically important correlation has been discovered between the HRV parameters and other basic clinical and paraclinical investigations and researches. This proved the existence of an important relation between the results obtained by Dantest and certain clinical, laboratory, physiological, and psychological examinations. Dantest, however, has the advantage of higher informativeness and easier practical application and execution.

It was proved that individuals with high values of health risk (according to Dantest) in several years are more likely to develop different pathological processes when compared to control check-ups.

HRV does not reflect the exact diagnosis, but rather the nonspecific anterior health risk in percentage (prior to the development of the disease process), since HRV measures the qualitative/numerical levels of stress and training, both of which are major risk factors. Chronically increased levels of health risk (for a time period longer than few months) can result in progress of serious diseases. Many scientific research papers and reports have been published on the topic of the reliability of HRV application in different branches of medicine – as described in the “HRV IN DIFFERENT MEDICAL AREAS” section.