Agitation Sensor Based on Facial Grimacing for Improved Sedation Management in Critical Care
| dc.contributor.author | Hann, C.E. | |
| dc.contributor.author | Becouze, P. | |
| dc.contributor.author | Chase, Geoff | |
| dc.contributor.author | Shaw, Geoff | |
| dc.contributor.author | Chen, X. | |
| dc.date.accessioned | 2008-09-23T23:05:42Z | |
| dc.date.available | 2008-09-23T23:05:42Z | |
| dc.date.issued | 2007 | en |
| dc.description.abstract | The effective delivery of sedation in critical care relies primarily on an accurate and consistent measure of a patient’s agitation level. However, current methods for assessing agitation are subjective and prone to error, often leading to over sedation or cycles between agitation and oversedation. This paper builds on previous work developing agitation sensors based on heart rate and blood pressure variability, and overall whole body motion. In this research, the focus is on real-time measurement of high resolution facial changes that are observed to occur in agitation. An algorithm is developed that measures the degree of facial grimacing from a single digital camera. The method is demonstrated on simulated patient facial motion to prove the concept. A consistent measure is obtained that is robust to significant random head movement and compares well against visual observation of different levels of grimacing. The method provides a basis for clinical validation. | en |
| dc.identifier.citation | Hann, C.E., Becouze, P., Chase, J.G., Shaw, G.M., Chen, X. (2007) Agitation Sensor Based on Facial Grimacing for Improved Sedation Management in Critical Care. Palmerston North, New Zealand: 2nd International Conference on Sensing Technology (ICST 2007), 26-28 Nov 2007. 6pp. | en |
| dc.identifier.uri | http://hdl.handle.net/10092/1624 | |
| dc.language.iso | en | |
| dc.publisher | University of Canterbury. Mechanical Engineering. | en |
| dc.rights.uri | https://hdl.handle.net/10092/17651 | en |
| dc.subject.marsden | Fields of Research::280000 Information, Computing and Communication Sciences::280200 Artificial Intelligence and Signal and Image Processing::280207 Pattern recognition | en |
| dc.title | Agitation Sensor Based on Facial Grimacing for Improved Sedation Management in Critical Care | en |
| dc.type | Conference Contributions - Published |