Name
Title | ||
|---|---|---|
Low-complexity wireless monitoring of respiratory movements using ultra-wideband impulse response estimation. |
Abstract | ||
|---|---|---|
In this paper, we present a comprehensive scheme for wireless monitoring of the respiratory movements in humans. Our scheme overcomes the challenges low signal-to-noise ratio, background clutter and high sampling rates. It is based on the estimation of the ultra-wideband channel impulse response. We suggest techniques for dealing with background clutter in situations when it might be time variant. We also present a novel methodology for reducing the required sampling rate of the system significantly while achieving the accuracy offered by the Nyquist rate. Performance results from simulations conducted with pre-recorded respiratory signals demonstrate the robustness of our scheme for tackling the above challenges and providing a low-complexity solution for the monitoring of respiratory movements. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.bspc.2013.11.004 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
compressed sensing,uwb,sparsity,nyquist rate,sampling,impulse response | Impulse response,Wireless,Telecommunications,Sampling (signal processing),Robustness (computer science),Real-time computing,Artificial intelligence,Compressed sensing,Computer vision,Clutter,Respiratory monitoring,Nyquist rate,Mathematics | Journal |
Volume | ISSN | Citations |
10 | 1746-8094 | 2 |
PageRank | References | Authors |
0.37 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Furrukh Sana | 1 | 2 | 1.72 |
| Tarig Ballal | 2 | 67 | 17.79 |
| Tareq Y. Al-Naffouri | 3 | 969 | 108.71 |
| Ibrahim Hoteit | 4 | 21 | 10.06 |