This review discusses the various applications of heart rate variability and the different linear, frequency domain, wavelet domain, and nonlinear techniques used for its analysis.
The heart is a key component of the human body, acting as a pump that transfers oxygenated and deoxygenated blood around the body. Like all other organs, it is susceptible to diseases and age. Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat- to-beat interval. Its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. In this paper we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.
ChuDuc et al. (Tue,) conducted a review in Cardiac diseases. Heart rate variability analysis was evaluated. This review discusses the various applications of heart rate variability and the different linear, frequency domain, wavelet domain, and nonlinear techniques used for its analysis.
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