Open AccessRobust heart rate estimation using combined ECG and PPG signal processing
Author(s) -
A. P. Zaretskiy,
Kirill S. Mityagin,
V. Tarasov,
D. N. Moroz,
A. S. Kuraleva
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/537/4/042077
Subject(s) - qrs complex , heart rate variability , waveform , photoplethysmogram , electrocardiography , pattern recognition (psychology) , medicine , computer science , cardiology , artificial intelligence , heart rate , blood pressure , filter (signal processing) , computer vision , telecommunications , radar
Heart rate variability (HRV) from recorded electrocardiograms (ECG) is a well-known diagnostic method for the assessment of autonomic nervous function of the heart, which is widely used to predict clinically relevant outcomes in the critical care setting, to risk stratify patients, and predict outcomes such as mortality. The morphological variations in the ECG waveform and the high degree of heterogeneity in the QRS complex often make it difficult to identify R waves, which may preclude the accurate analysis for HRV. Photoplethysmographic (PPG) signal can provide information about both the cardiovascular and respiratory systems and have extremely high degree of correlation with ECG during cardiac cycle. In this paper, we developed robust algorithm for high-resolution inter-beat waveform extraction using combined ECG and PPG analysis, which is highly needed for accurate HRV estimation. The simulation results showed high performance for inter-beat waveform detection in different cases that identifies missing/extra peaks in the QRS detection algorithm.