Detection of patient's bed statuses in 3D using a Microsoft Kinect
Li, Y; Berkowitz, L; Noskin, G; Mehrotra, S
| HERO ID | 3539553 |
|---|---|
| In Press | No |
| Year | 2014 |
| Title | Detection of patient's bed statuses in 3D using a Microsoft Kinect |
| Authors | Li, Y; Berkowitz, L; Noskin, G; Mehrotra, S |
| Journal | IEEE Engineering in Medicine and Biology Society. Conference Proceedings |
| Volume | 2014 |
| Page Numbers | 5900-5903 |
| Abstract | Patients spend the vast majority of their hospital stay in an unmonitored bed where various mobility factors can impact patient safety and quality. Specifically, bed positioning and a patient's related mobility in that bed can have a profound impact on risks such as pneumonias, blood clots, bed ulcers and falls. This issue has been exacerbated as the nurse-per-bed (NPB) ratio has decreased in recent years. To help assess these risks, it is critical to monitor a hospital bed's positional status (BPS). Two bed positional statuses, bed height (BH) and bed chair angle (BCA), are of critical interests for bed monitoring. In this paper, we develop a bed positional status detection system using a single Microsoft Kinect. Experimental results show that we are able to achieve 94.5% and 93.0% overall accuracy of the estimated BCA and BH in a simulated patient's room environment. |
| Doi | 10.1109/EMBC.2014.6944971 |
| Pmid | 25571339 |
| Wosid | WOS:000350044705222 |
| Is Certified Translation | No |
| Dupe Override | No |
| Is Public | Yes |
| Language Text | English |