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1.上海大学 机电工程与自动化学院,上海 200072
2.中国科学院 苏州生物医学工程技术研究所,江苏 苏州 215163
3.苏州大学 电子信息学院,江苏 苏州 215006
[ "郭健(1993-),男,江苏泰州人,硕士研究生,2012年于苏州大学获得学士学位,主要从事医用电子方面的研究。E-mail:scguoj@i.shu.edu.cn" ]
陈晓禾(1976-),男,北京人,博士,研究员,2000年于清华大学获得学士学位,2003年于美国南伊利诺大学获得硕士学位,2007年于美国密苏里科技大学获得博士学位,主要从事高速电路设计和电子工程设计领域的研究。E-mail:chenxh@sibet.ac.cnCHEN Xiao-he, E-mail: chenxh@sibet.ac.cn
收稿日期:2018-12-24,
录用日期:2019-2-25,
纸质出版日期:2019-06-15
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郭健, 陈雨行, 王丽荣, 等. 非接触式呼吸与心率信号采集系统[J]. 光学 精密工程, 2019,27(6):1354-1361.
Jian GUO, Yu-hang CHEN, Li-rong WANG, et al. Non-contact respiratory rate and heart rate signal acquisition system[J]. Optics and precision engineering, 2019, 27(6): 1354-1361.
郭健, 陈雨行, 王丽荣, 等. 非接触式呼吸与心率信号采集系统[J]. 光学 精密工程, 2019,27(6):1354-1361. DOI: 10.3788/OPE.20192706.1354.
Jian GUO, Yu-hang CHEN, Li-rong WANG, et al. Non-contact respiratory rate and heart rate signal acquisition system[J]. Optics and precision engineering, 2019, 27(6): 1354-1361. DOI: 10.3788/OPE.20192706.1354.
为实现卧床病员生命状态的无感实时监测,设计了一种非接触式呼吸率与心率监测系统。首先,根据心脏射血收缩过程的力学特性,选择灵敏度高、稳定性好的压电陶瓷传感器采集心冲击力学信号。对信号进行去噪,滤波放大等处理,通过数字化采集得到心冲击图(Ballistocardiogram,BCG)。其次,通过对心冲击图进行平滑滤波提取呼吸信号,利用快速傅氏变换(FFT)获取呼吸信号频率。采用带通滤波器去除BCG信号的呼吸包络以及高频干扰,获取BCG信号的单位时间J波波峰数,推算出心率值。最后,为验证系统的准确性与一致性,与BIOPAC采集的呼吸及心电图(Electrocardiogram,ECG)信号进行比对,结果表明本系统呼吸误差率小于4.5%,心率误差率小于9.7%。通过Bland-Altman分析,表明监测系统的心率测算准确度与BIOPAC具有较好的一致性。
A non-contact respiratory and heart rate monitoring system was designed to monitor bedridden patients. Initially
according to the mechanical properties of the cardiac ejection contraction process
piezoelectric ceramic sensors with high sensitivity and good stability were selected to acquire ballistocardiography (BCG) signals. The collected signal was then desiccated
filtered and amplified; it was then digitized to obtain a heart impact diagram. A respiratory signal was then extracted from the cardiogram with smooth filtering
and the respiratory rate signal was obtained via an FFT transformation. The respiratory envelope and high-frequency interference of the BCG signal were removed using a band-pass filter
and the j-wave peak measurement of the BCG signal was obtained to calculate the heart rate. Finally
to verify the accuracy and consistency of the system
it was compared with respiratory data collected by BIOPAC and ECG signals. The respiratory error rate of the system is less than 4.5% and the heart rate error is 9.7%. A Bland-Altman analysis indicates that the heart rate measurement and accuracy computed by the monitoring system are consistent with those of BIOPAC.
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