Name
Abstract | ||
|---|---|---|
Vital signs such as heart rate and heartbeat interval are currently measured by electrocardiograms (ECG) or wearable physiological monitors. These techniques either require contact with the patient's skin or are usually uncomfortable to wear, rendering them too expensive and user-unfriendly for daily monitoring. In this paper, we propose a new non-invasive technology to generate an Acousticcardiogram (ACG) that precisely monitors heartbeats using inaudible acoustic signals. ACG uses only commodity microphones and speakers commonly equipped on ubiquitous off-the-shelf devices, such as smartphones and laptops. By transmitting an acoustic signal and analyzing its reflections off human body, ACG is capable of recognizing the heart rate as well as heartbeat rhythm. We employ frequency modulated sound signals to separate reflection of heart from that of background motions and breath, and continuously track the phase changes of the acoustic data. To translate these acoustic data into heart and breath rates, we leverage the dual microphone design on COTS mobile devices to suppress direct echo from speaker to microphones, identify heart rate in frequency domain, and adopt an advanced algorithm to extract. individual heartbeats. We implement ACG on commercial devices and validate its performance in real environments. Experimental results demonstrate ACG monitors user's heartbeat accurately, with median heart rate estimation error of 0.6 beat per minute (bpm), and median heartbeat interval estimation error of 19 ms. |
Year | Venue | Field |
|---|---|---|
2018 | IEEE INFOCOM | Frequency domain,Heartbeat,Computer science,Wearable computer,Computer network,Sonar,Real-time computing,Mobile device,Median Heart Rate,Heart rate,Microphone |
DocType | ISSN | Citations |
Conference | 0743-166X | 3 |
PageRank | References | Authors |
0.39 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kun Qian | 1 | 114 | 6.53 |
| Chenshu Wu | 2 | 1036 | 52.62 |
| Fu Xiao | 3 | 115 | 35.24 |
| Yue Zheng | 4 | 70 | 10.70 |
| Yi Zhang | 5 | 3 | 0.39 |
| Zheng Yang | 6 | 2341 | 108.35 |
| Yunhao Liu | 7 | 8810 | 486.66 |