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基于单频超声的智能手机呼吸率估计

Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones.

作者信息

Ge Linfei, Zhang Jin, Wei Jing

机构信息

Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.

Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.

出版信息

Comput Math Methods Med. 2018 May 6;2018:3675974. doi: 10.1155/2018/3675974. eCollection 2018.

Abstract

Respiration monitoring is helpful in disease prevention and diagnosis. Traditional respiration monitoring requires users to wear devices on their bodies, which is inconvenient for them. In this paper, we aim to design a noncontact respiration rate detection system utilizing off-the-shelf smartphones. We utilize the single-frequency ultrasound as the media to detect the respiration activity. By analyzing the ultrasound signals received by the built-in microphone sensor in a smartphone, our system can derive the respiration rate of the user. The advantage of our method is that the transmitted signal is easy to generate and the signal analysis is simple, which has lower power consumption and thus is suitable for long-term monitoring in daily life. The experimental result shows that our system can achieve accurate respiration rate estimation under various scenarios.

摘要

呼吸监测有助于疾病的预防和诊断。传统的呼吸监测要求用户在身体上佩戴设备,这对他们来说很不方便。在本文中,我们旨在设计一种利用现成智能手机的非接触式呼吸率检测系统。我们利用单频超声作为介质来检测呼吸活动。通过分析智能手机中内置麦克风传感器接收到的超声信号,我们的系统可以得出用户的呼吸率。我们方法的优点是发射信号易于产生且信号分析简单,具有较低的功耗,因此适合在日常生活中进行长期监测。实验结果表明,我们的系统在各种场景下都能实现准确的呼吸率估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e7/5960545/369bd11d24af/CMMM2018-3675974.001.jpg

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