Name
Abstract | ||
|---|---|---|
Aim of this study is to extract near-continuously respiratory rate by a contactless method. An industrial camera was used to record subjects face. Video data were processed offline to derive the video-photoplethysmographic (videoPPG) signal. Three features were extracted from videoPPG and finger PPG signal: pulse rate variability (PRV), pulse amplitude variability (PAV) and pulse width variability (PWV). A combination of these methods has been exploited to estimate the respiratory rate for each time window of 5 second. The results showed relative error with median around 0.5% and interquartile range of 5% both for finger PPG and videoPPG system. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.22489/CinC.2017.028-317 | 2017 Computing in Cardiology (CinC) |
Keywords | Field | DocType |
respiratory rate detection,contactless sensor,industrial camera,video data,video-photoplethysmographic signal,pulse width variability,videoPPG,finger PPG | Pulse-width modulation,Respiratory rate,Acoustics,Pulse-amplitude modulation,Approximation error,Pulse rate variability,Physics | Conference |
Volume | ISSN | ISBN |
44 | 2325-8861 | 978-1-5386-4555-0 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luca Iozzia | 1 | 0 | 1.01 |
| Jesús Lázaro | 2 | 62 | 16.25 |
| Eduardo Gil | 3 | 61 | 19.54 |
| Luca Cerina | 4 | 2 | 4.52 |
| Luca M. Mainardi | 5 | 1 | 0.70 |
| P Laguna | 6 | 255 | 74.15 |