Non-contact respiratory rate and heart rate signal acquisition system

Jian GUO; Yu-hang CHEN; Li-rong WANG; Yang WEI; Yu GUO; Ye-ming ZHAO; Li-lan LIU; Xiao-he CHEN

doi:10.3788/OPE.20192706.1354

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Non-contact respiratory rate and heart rate signal acquisition system

Life Science Instrument | 更新时间：2020-08-13

- Non-contact respiratory rate and heart rate signal acquisition system
- Optics and Precision Engineering Vol. 27, Issue 6, Pages: 1354-1361(2019)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20192706.1354
  CLC： TP212
- Received：24 December 2018，
  
  Accepted：25 February 2019，
  
  Published：15 June 2019
- 稿件说明：
移动端阅览
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：

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.

摘要

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。

Abstract

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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