Lei Wang, Wei Li, Ke Sun, Fusang Zhang, Tao Gu, Chenren Xu, Daqing Zhang
{"title":"LoEar: Push the Range Limit of Acoustic Sensing for Vital Sign Monitoring","authors":"Lei Wang, Wei Li, Ke Sun, Fusang Zhang, Tao Gu, Chenren Xu, Daqing Zhang","doi":"10.1145/3550293","DOIUrl":null,"url":null,"abstract":"Acoustic sensing has been explored in numerous applications leveraging the wide deployment of acoustic-enabled devices. However, most of the existing acoustic sensing systems work in a very short range only due to fast attenuation of ultrasonic signals, hindering their real-world deployment. In this paper, we present a novel acoustic sensing system using only a single microphone and speaker, named LoEar, to detect vital signs (respiration and heartbeat) with a significantly increased sensing range. We first develop a model, namely Carrierforming , to enhance the signal-to-noise ratio (SNR) via coherent superposition across multiple subcarriers on the target path. We then propose a novel technique called Continuous-MUSIC (Continuous-MUltiple SIgnal Classification) to detect a dynamic reflections, containing subtle motion, and further identify the target user based on the frequency distribution to enable Carrierforming . Finally, we adopt an adaptive Infinite Impulse Response (IIR) comb notch filter to recover the heartbeat pattern from the Channel Frequency Response (CFR) measurements which are dominated by respiration and further develop a peak-based scheme to estimate respiration rate and heart rate. We conduct extensive experiments to evaluate our system, and results show that our system outperforms the state-of-the-art using commercial devices, i.e., the range of respiration sensing is increased from 2 m to 7 m, and the range of heartbeat sensing is increased from 1.2 m to 6.5 m.","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"65 1","pages":"145:1-145:24"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3550293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Acoustic sensing has been explored in numerous applications leveraging the wide deployment of acoustic-enabled devices. However, most of the existing acoustic sensing systems work in a very short range only due to fast attenuation of ultrasonic signals, hindering their real-world deployment. In this paper, we present a novel acoustic sensing system using only a single microphone and speaker, named LoEar, to detect vital signs (respiration and heartbeat) with a significantly increased sensing range. We first develop a model, namely Carrierforming , to enhance the signal-to-noise ratio (SNR) via coherent superposition across multiple subcarriers on the target path. We then propose a novel technique called Continuous-MUSIC (Continuous-MUltiple SIgnal Classification) to detect a dynamic reflections, containing subtle motion, and further identify the target user based on the frequency distribution to enable Carrierforming . Finally, we adopt an adaptive Infinite Impulse Response (IIR) comb notch filter to recover the heartbeat pattern from the Channel Frequency Response (CFR) measurements which are dominated by respiration and further develop a peak-based scheme to estimate respiration rate and heart rate. We conduct extensive experiments to evaluate our system, and results show that our system outperforms the state-of-the-art using commercial devices, i.e., the range of respiration sensing is increased from 2 m to 7 m, and the range of heartbeat sensing is increased from 1.2 m to 6.5 m.
声学传感已经在许多应用中进行了探索,这些应用利用了声学启用设备的广泛部署。然而,由于超声波信号的快速衰减,大多数现有的声学传感系统只能在很短的范围内工作,这阻碍了它们在现实世界中的部署。在本文中,我们提出了一种新的声学传感系统,仅使用一个麦克风和扬声器,称为LoEar,以显著增加的传感范围检测生命体征(呼吸和心跳)。我们首先开发了一个模型,即载波成形,通过目标路径上多个子载波的相干叠加来提高信噪比(SNR)。然后,我们提出了一种名为Continuous-MUSIC (Continuous-MUltiple SIgnal Classification)的新技术来检测包含细微运动的动态反射,并根据频率分布进一步识别目标用户,从而实现载波成形。最后,我们采用自适应无限脉冲响应(IIR)梳状陷波滤波器从通道频率响应(CFR)测量中恢复心跳模式,通道频率响应(CFR)测量以呼吸为主,并进一步开发了基于峰值的方案来估计呼吸速率和心率。我们进行了大量的实验来评估我们的系统,结果表明我们的系统优于目前使用的商业设备,即呼吸传感范围从2米增加到7米,心跳传感范围从1.2米增加到6.5米。