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| Content Provider | ACM Digital Library |
|---|---|
| Author | Nguyen, Phuc Halbower, Ann C. Vu, Tam Zhang, Xinyu |
| Abstract | An unobtrusive and continuous estimation of breathing volume could play a vital role in health care, such as for critically ill patients, neonatal ventilation, post-operative monitoring, just to name a few. While radar-based estimation of breathing rate has been discussed in the literature, estimating breathing volume using wireless signal remains relatively intact. With the presence of patient body movement and posture changes, long-term monitoring of breathing volume at fine granularity is even more challenging. In this work, we propose for the first time an autonomous system that monitors a patient's breathing volume with high resolution. We discuss the key research components and challenges in realizing the system. We also present an initial system design encompassing a continuous wave radar, motion tracking and control system, and a set of methods to accurately derive breathing volume from the reflected signal and to address challenges caused by body movement and posture changes. Our implementation shows promising results in estimating breathing volume with fine granularity. |
| Starting Page | 266 |
| Ending Page | 268 |
| Page Count | 3 |
| File Format | PDF EPUB |
| ISBN | 9781450336192 |
| DOI | 10.1145/2789168.2795177 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-09-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Breathing volume monitoring Mobile health Radar technique Fine-grained estimation |
| Content Type | Text |
| Resource Type | Article |
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