An improved algorithm for respiration signal extraction from electrocardiogram measured by conductive textile electrodes using instantaneous frequency estimation

• Published in: Medical & biological engineering & computing Vol. 46; no. 2; pp. 147 - 158
• Main Authors: Park, Sung-Bin, Noh, Yeon-Sik, Park, Sung-Jun, Yoon, Hyoung-Ro
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.02.2008; Springer Nature B.V
• Subjects: Adhesives; Algorithms; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Computer Applications; Electrocardiography; Electrocardiography - instrumentation; Electrocardiography - methods; Electrodes; Health care; Hilbert space; Home Care Services; Human Physiology; Humans; Imaging; Male; Medical research; Methods; Original; Original Article; Radiology; Respiration; Respiratory Mechanics; Signal processing; Signal Processing, Computer-Assisted; Studies; Textiles; Conductive textile electrodes in bed; Hilbert transform; ECG-derived respiration; Instantaneous frequency; Home healthcare
• ISSN: 0140-0118; 1741-0444; 1741-0444
• DOI: 10.1007/s11517-007-0302-y

In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation ( r 2  > 0.8) with the signal acquired from the chest-belt respiration sensor.