Heart rate variability (HRV) analysis using DSP for the detection of myocardial infarction

Abstract

Spectral analysis of heart rate fluctuations are commonly used as quantitative and non-invasive techniques for the study of short-term cardiovascular control functions. Such fluctuations contain key information relating to sympathetic and parasympathetic activity within the cardiovascular control system. This employs ECG complexes to determine the R-wave occurrences and IBI interval lengths. It has been shown that the variations in the interbeat interval time series show key frequency-specific properties. This work demonstrates high precision algorithms (Matlab and MikroC algorithms) and a state of the art “interpolation process”, to accurately detect R-points and translate them into uniformly sampled signals. Power Spectrum analysis of HRV signals has shown distinct differences between MI patients versus normal subjects. This provides the opportunity to quantify ANS imbalances, leading to distinct classification of Myocardial infracted patients from normal subjects. For real time implementation, a dsPIC microcontroller was programmed using the “MikroC” software.