北京生物医学工程

一种基于可穿戴设备和智能手机的呼吸监测系统设计

Design of a respiratory monitoring system based on wearable devices and smart phone

作者：刘永凯孙珅史文飞吴水才

单位：北京工业大学生命科学与生物工程学院(北京 100124)

关键词：可穿戴设备；智能手机；低功耗蓝牙；呼吸监测；监护系统

分类号：R318.6

出版年·卷·期（页码）：2019·38·4（417-423）

摘要：

目的呼吸运动是人体重要的生理活动之一，呼吸频率的变化能发映人体生理状况的好坏，因此呼吸频率的监测对于健康监护具有重要意义。方法本研究设计一种基于可穿戴设备和智能手机的呼吸监测系统。可穿戴式设备的主控芯片采用低功耗蓝牙芯片nrf52832，利用加速度传感器MPU6050采集人体呼吸运动的加速度信号，利用低功耗蓝牙方式与智能手机进行通信；智能手机端软件能够实时接收可穿戴式设备发送过来的呼吸运动数据，利用后台运行的呼吸检测算法计算出呼吸频率等相关参数，并绘制出呼吸运动波形。此外，智能手机可以对接收到的呼吸运动数据进行存储，可对用户的呼吸活动进行长期的分析研究。结果 (1)穿戴式设备工作电流11 mA，广播电流12 mA，待机电流10 mA，工作电压3.3 V，功率约为33 mW；(2)呼吸检测的准确率在95%以上；(3)智能手机界面能够实时显示呼吸运动的加速度波形和呼吸频率。结论本研究设计的系统具有方便佩戴、功耗低和呼吸检测准确性高等优点，能够适用于家庭等场所进行呼吸监护，满足人们对日常健康监护的需求。

Objective Breathing is one of the important physiological activities of human body, the change of respiration frequency can reflect the quality of human body, so the monitoring of respiratory frequency is of great significance for health monitoring. Methods In this study, a respiratory monitoring system based on wearable devices and smart phone was designed. The main control chip of wearable device adopts low power Bluetooth chip nrf52832, uses acceleration sensor MPU6050 to collect acceleration signal of human breathing motion, and communicates with smart phone by low power Bluetooth method. Smartphone software can receive breathing motion data sent by wearable devices in real time. The smartphone calculates the breathing frequency and other related parameters by using the breathing detection algorithm of the service running in the background, and draws the respiratory motion waveform. In addition, smart phone can store incoming breathing motion data for long-term analysis and research on the user's breathing activity. Results (1) wearable device operating current 11 mA, broadcast current 12 mA, standby current 10 mA, working voltage 3.3 V, power is about 33 mW; (2) The accuracy of respiratory testing is above 95%; (3) The smartphone interface displays the acceleration waveform and respiratory rate of the breathing movement in real time. Conclusions The system designed in this study has the advantages of easy wearing, low power consumption and high breath detection accuracy. It can be used for respiratory monitoring in homes and other places to meet people's needs for daily health monitoring.

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