The paper deals with the application of entropy and energy measure of fuzziness to processing heart rate variability (HRV) signal. The signal is a source of important information about mechanisms regulating the heart activity. Recently it has been proved that tracing the changes of the signal is of great significance in predicting the course of numerous diseases. The variability of the heart rhythm is illustrated by means of several indices. The common feature of most indices is an assumption of the stationarity of the HRV signal. Investigations show that the majority of biological processes, including the HRV signal, are characterized by nonstationarity or at most quasi-stationarity, which significantly limits the reliability of the above mentioned indices. As a result, new methods without the above limitations have been sought, also taking into account new results in engineering. This paper presents the idea of a fuzzy signal and methods of determining the energy and entropy measures of fuzziness of such a signal. The theoretical considerations have been illustrated with digital processing of the real HRV signal.

Keywords: fuzzy signal, measures of fuzziness, processing of HRV signal