Estimation of Respiratory Rate Based on Data Fusion Using Electrocardiogram and Pulse Wave#br#
1 Institute of Biomedical Engineering, Shandong University School of Medicine, Jinan 250012, China
2 Department of Cardiology, Jinan Fourth Hospital, Jinan 250031, China
Abstract：In this paper, an algorithm was proposed to estimate respiratory rate using electrocardiogram (ECG) and pulse wave (PW), based on multiple sensor data fusion with Kalman filter. Respiratory signal was acquired separately from the RR interval series and the R absolute amplitude of ECG, as well as from the beat cycles of PW. The respiratory rate was estimated by AR model. Signal quality indices (SQIs) were acquired based on signal waveform, rhythm and spectral features. Then the respiratory rate was fused based on SQIs and residuals of Kalman filter. The signals were sampled from 14 volunteers. The results indicate that the fused respiratory rate performs better than those derived from ECG and PW directly. Compared to the reference of a piezoresistive sensor, the estimation error of data fusion method is (-0.03±2.78) breaths/min. It is much less than both ECG-derived rates (RR interval series: (0.62±3.30)breaths/min; R absolute amplitude: (0.42±3.47) breaths/min) and PW-derived rate (-0.17±2.69) breaths/min). In conclusion, the multiple data fusion method is noise-resisted and suitable for respiratory rate estimation.
邓宝芸1 潘燕1 孟延1 刘兵2 孙文红1 张玉华1 戚焰1 李桥1*. 基于心电和脉搏波数据融合的呼吸率估计[J]. 中国生物医学工程学报, 2012, 31(2): 211-216.
DENG Bao Yun1 PAN Yan1 MENG Yan1 LIU Bing2 SUN Wen Hong1 ZHANG Yu Hua1 QI Yan1 . Estimation of Respiratory Rate Based on Data Fusion Using Electrocardiogram and Pulse Wave#br#. journal1, 2012, 31(2): 211-216.
