Liu Chenqin, Yuan Sinian, Lin Gaozang, Cai Shijie, Ye Jilun, Zhang Xu, Jin Hao
Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, 518060.
Shenzhen Key Lab for Biomedical Engineering, Shenzhen, 518060.
Zhongguo Yi Liao Qi Xie Za Zhi. 2022 Jul 30;46(4):368-372. doi: 10.3969/j.issn.1671-7104.2022.04.004.
Breathing is of great significance in the monitoring of patients with obstructive sleep apnea hypopnea syndrome, perioperative monitoring and intensive care. In this study, a respiratory monitoring and verification system based on optical capacitance product pulse wave (PPG) is designed, which can synchronously collect human PPG signals. Through algorithm processing, the characteristic parameters of PPG signal are calculated, and the respiratory signal and respiratory frequency can be extracted in real time. In order to verify the accuracy of extracting respiratory signal and respiratory rate by the algorithm, the system adds the nasal airflow respiratory signal acquisition module to synchronously collect the nasal airflow respiratory signal as the standard signal for comparison and verification. Finally, the root mean square error between the respiratory rate extracted by the algorithm from the pulse wave and the standard respiratory rate is only 1.05 times/min.
呼吸在阻塞性睡眠呼吸暂停低通气综合征患者的监测、围手术期监测和重症监护中具有重要意义。本研究设计了一种基于光电容积脉搏波（PPG）的呼吸监测与验证系统，该系统能够同步采集人体PPG信号。通过算法处理，计算出PPG信号的特征参数，并实时提取呼吸信号和呼吸频率。为了验证算法提取呼吸信号和呼吸频率的准确性，该系统增加了鼻气流呼吸信号采集模块，同步采集鼻气流呼吸信号作为标准信号进行对比验证。最终，算法从脉搏波中提取的呼吸频率与标准呼吸频率之间的均方根误差仅为1.05次/分钟。
