Interpretation of Premature Ventricular Abnormality based on HRV Analysis

Abstract

Cardiac abnormality estimation can be performed using Heart rate variability (HRV) parameters acquired from the ECG signal. HRV analysis offers different approaches for assessing inputs into the cardiac rhythm non-invasively. For the present investigation, a total of ten participants including males and females of age group 19–25 years have participated voluntarily. RR-intervals have been assessed from a preprocessed ECG signal, which is further employed for calculating HRV parameters. The present paper is an effort to identify the heart-beat abnormality especially PVCs based on HRV parameters. Time-domain parameters like SDNN, mean HR, RMSSD as well as frequency domain parameters LFnu, HFnu and the ratio LF/HF have been incorporated for this study. Results reveal that the significant difference in the time-domain and frequency-domain HRV parameters among participants is due to the presence of premature ventricular contraction (PVC) in the ECG signal. Additionally, ECG signals have been identified and classified using BIOP AC MP45 student lab software for the validation of PVC. Hence, alteration of HRV parameters can be directly interpreted for identification of the presence of PVCs.