Noise Tolerant Heart Rate Extraction Algorithm Using Short-Term Autocorrelation for Wearable Healthcare Systems

Shintaro IZUMI  Masanao NAKANO  Ken YAMASHITA  Yozaburo NAKAI  Hiroshi KAWAGUCHI  Masahiko YOSHIMOTO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E98-D   No.5   pp.1095-1103
Publication Date: 2015/05/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDP7161
Type of Manuscript: PAPER
Category: Biological Engineering
Keyword: 
autocorrelation,  biomedical signal processing,  electrocardiography,  heart rate extraction,  noise tolerance,  

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Summary: 
This report describes a robust method of instantaneous heart rate (IHR) extraction from noisy electrocardiogram (ECG) signals. Generally, R-waves are extracted from ECG using a threshold to calculate the IHR from the interval of R-waves. However, noise increases the incidence of misdetection and false detection in wearable healthcare systems because the power consumption and electrode distance are limited to reduce the size and weight. To prevent incorrect detection, we propose a short-time autocorrelation (STAC) technique. The proposed method extracts the IHR by determining the search window shift length which maximizes the correlation coefficient between the template window and the search window. It uses the similarity of the QRS complex waveform beat-by-beat. Therefore, it has no threshold calculation process. Furthermore, it is robust against noisy environments. The proposed method was evaluated using MIT-BIH arrhythmia and noise stress test databases. Simulation results show that the proposed method achieves a state-of-the-art success rate of IHR extraction in a noise stress test using a muscle artifact and a motion artifact.