Spectral independent component analysis of heart rate variability

SUMMARY Formal mathematical procedure of developed Spectral Independent Component Analysis (SICA) of heart rate variability (HRV) allows to obtain no more than three components forming the rhythmogramm of healthy person. This fact rationally represents physiological hypotheses about regulation systems taking part in forming HRV phenomenon. Applying SICA to HRV approves itself on timing intervals form 3 to 15 minutes. Вreaking the low limit of this timing interval causes essential worsening of quality of ICA components forming the rhythmogramm. Optimal application of SICA for splitting initial registered HRV signal into components is using SICA with five-minute HRV registering protocol. KEY WORDS: rythmogramm, heart rate variability, independent component analysis The phenomenon of heart rate variability (HRV) was noticed by physicians long ago: first mention about HRV in European scientific literature attributed to Stephen Hales in 1733. However, wide development of HRV-based diagnostic methods and their applications in medicine dates from the end of last century, because of development of high-precision digital computer electrocardiography (ECG) and standardization of HRV-technology, carried out by the workgroup of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 5-minute, 15-minute and 24-hour protocols are most often used for researches of heart rate variability. In HRV analysis the most valuable information can be achieved with the application of dimensional-spectral methods: quick transformation by Furrier, autoregressive, and others. Important spectrum descriptions are: its power, and powers of its separate zones (domains). In 5-minute and 15-minute protocols, 3 inherent zones can be differed: VLF - zone of very low frequencies (0.0033-0.04 Hz), LF - zone of low frequencies (0.04-0.15 Hz), HF - zone of high frequencies (0.25-0.4 Hz) [1]. Thus, clear correlation of the power of every spectral domain with its corresponding regulating unit of an organism was determined. Parasympathic link of the vegetative nervous organism regulation influences fast rate variations of a cardiac rhythm (HF); sympathic link of the vegetative nervous organism regulation influences medium rate variations of a cardiac rhythm (LF); humoral link of the neurohumoral organism regulation influences slow rate variations (VLF). At the same time, traditional approach has certain drawbacks, generally related to formal techniques of selecting regulation domains in the spectrum. Essential progress in solution of the current problem can be attained by application of more complex mathematical methods, which allow separating of initial registered rhythmogram into independent components. Two non-formal approach in selecting spectral-regulating domains in HRV can be noted marked: - statistical methods of analysis, based on common approaches in time series analysis; - mathematical modeling, representing phy-siological features of regulating processes of heart activity. The article is devoted to statistical approach that is based on the method of separating registered composite rhythmogram to its independent components, each formed by corresponding regulating unit of an organism. It’s clear that the application of well known methods (such as factor analysis – principal component analysis) that use a linear decorellation of components, for this purpose is limited and almost incompetent, because of essential non-linearity of the phenomenon being considered - the heart rate variability. The appearance of non-linear statistical analysis method - independent component analysis (ICA) [2] and its successful development in solving of composite medical problems (for example, in encephalogram analysis) show it being very perspective for application in HRV analysis.