Extraction of underlying genuine heart rate variability using adaptive signal canceling algorithm

This paper proposes a method for extracting underlying genuine heart rate fluctuations, separating them from distinct respiratory and blood pressure originating fluctuations. Heart rate fluctuations, instantaneous lung volume and blood pressure changes are simultaneously recorded from nine normal subjects aged from 20-24 years old. A signal cancellation scheme together with the adaptive RLS algorithm has been applied to the data to cancel respiration and blood pressure originated changes in the heart rate variability. It was shown that after cancellation, the power spectrum represented a consistent monotonic 1/f ^a type pattern, removing uncertain large individual variations, which enables a clear interpretation of heart rate variability