An Instantaneous Frequency Based Approach to Estimate Heart Rate and Calculate Heart Rate Variability Metrics
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Abstract
An emerging diagnostic tool for detecting heart and physiological conditions is heart rate variability (HRV). Copious research continuously discovers relationships between heart rate variability metrics and physiological functions and cardiac health. The first step in calculating HRV metrics is calculating heart rate. Heart rate is typically calculated using the interval between R peaks in an EKG signal. Consequently, heart rate measurements rely on the presence of distinctive R peaks and the accurate detection of them. The study is motivated by the drawbacks associated with using R peaks to calculate instantaneous heart rate.
In this study we present an alternative method (that does not rely on R peaks) based on the concept of instantaneous frequency to estimate heart rate from electrocardiogram (EKG) signals. The EKG signal is filtered to extract constituent frequency components that correlate with the instantaneous heart rate. The filtered signal is then fed into an algorithm that outputs a signal that shows the variation of the instantaneous heart rate with time. This output signal contains noise due to the behavior of the algorithm at zero crossings of the filtered EKG signal. Two methods for filtering the output signal are also presented in the study.
The proposed method was able to successfully estimate the instantaneous heart rate and allowed the subsequent calculation of frequency domain HRV metrics. This method potentially provides more information for HRV analysis and addresses the drawbacks associated with methods based on R peak detection.