估算心率和呼吸频率的智能手机系统

Amit Nayak;Miodrag Bolic
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摘要

在这篇短文中,我们介绍了一种新方法,即使用不固定在仰卧位受试者胸部的智能手机来获取心跳和呼吸信号,并同时估算心跳和呼吸频率。我们收集了三轴加速计、陀螺仪和磁力计信号,并进行了传感器融合,以提取用户的呼吸信号和呼吸频率。我们使用隐马尔可夫模型来分割心球/心肌扫描仪信号并提取心率。智能手机应用通过呼吸带测量和心电图测量进行了验证。我们修改并提出了几个适合地震心动图信号的信号质量指标。总体结果表明,该应用能准确估计呼吸和心率,呼吸和心率的平均误差最小分别为 2.52% 和 2.33%。这项工作为使用廉价的普适性设备进行生命体征估计迈出了一大步。
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Smartphone System for Heart Rate and Breathing Rate Estimation
In this short article, we present a new method to use a smartphone placed unattached on a subject’s chest in the supine position to obtain heartbeat and breathing signals and estimate heart and breathing rates, simultaneously. We collected 3-axis accelerometer, gyroscope, and magnetometer signals and performed sensor fusion to extract a user’s breathing signal and breathing rate. A hidden Markov model was used to segment the ballistocardiograph/seismocardiograph signals and extract the heart rate. The smartphone application was verified against breathing belt measurements and electrocardiogram measurements. We modified and proposed several suitable signal quality metrics for seismocardiograph signals. The overall results show that the application accurately estimated the breathing and heart rates, achieving a minimum mean percent error of 2.52% for breathing and 2.33% for heart rate. This work is a big step forward for vital sign estimation using inexpensive pervasive devices.
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