Computer Engineering and Applications ›› 2022, Vol. 58 ›› Issue (5): 302-308.DOI: 10.3778/j.issn.1002-8331.2009-0242

• Engineering and Applications • Previous Articles    

Design and Implementation of Non-invasive Sleeping Breaths Monitoring System

YANG Jiafeng, TONG Jijun, JIANG Lurong, PAN Zheyi   

  1. 1.School of Information, Zhejiang ?Sci-Tech ?University, Hangzhou 310000, China
    2.Department of Information, China Coast Guard Hospital of the People’s Armed Police Force, Jiaxing, Zhejiang 314000, China
  • Online:2022-03-01 Published:2022-03-01



  1. 1.浙江理工大学 信息学院,杭州 310000
    2.武警海警总队医院 信息科,浙江 嘉兴 314000

Abstract: Fulling the sleep and respiratory monitoring needs of people in special areas such as nursing homes and hospitals, a non-invasive flexible pressure-sensitive sleeping breaths monitoring system is designed. The system uses hardware circuit design to collect the breathing signals of the human body during sleep, and perform preprocessing such as denoising and detrending. In the hardware terminal, the breathing type is distinguished by the characteristics of the amplitude and period of the breathing signal, and it is determined in real time whether an apnea has occurred. The time and duration of the pause are recorded, and the data is transferred to the smartphone through the Bluetooth module. Real-time waveform can be drawn on the mobile APP. Smartphone can upload the data to the cloud platform. A PC software can obtain data from the cloud platform, draw fitted breathing signal curves, and determine and record sleeping data. After experimental tests, the number of breathes reported by the system is in rough consistency with the real value while also accurately detecting apnea, which meets the requirements for long-term sleeping breaths monitoring.

Key words: non-invasive monitoring system, embedded chip, apnea syndrome, discrimination of respiratory type

摘要: 根据养老院、医院等特殊区域人群的睡眠呼吸监护需求,设计了非入侵式柔性压感睡眠呼吸监测系统。系统通过硬件电路设计,采集人体睡眠时的呼吸信号,并进行消噪、去趋势等预处理。在硬件终端中通过呼吸信号的幅度和周期的特征区分呼吸类别,并实时判断是否发生了呼吸暂停,记录暂停的时刻与持续时长,并将数据通过蓝牙传至手机,在手机APP上可绘制实时波形,手机把数据上传至云平台。PC端软件可从云平台获取数据,绘制拟合呼吸信号曲线,判定记录睡眠数据。经实验测试,系统判定呼吸次数与实际基本一致,并可准确判断呼吸暂停情况,满足长程实现睡眠呼吸监测的要求。

关键词: 非入侵式监护系统, 嵌入式芯片, 呼吸暂停综合征, 呼吸类型判别