|
Automated
Detection of Pain |
Recent advances in automated facial expression recognition
technology open new possibilities for clinical research, assessment, and
intervention systems. Integration of such technology in clinical research is
both timely and crucial. The goal of this
research is to develop automated system for measurement of pain from facial
expression using computer vision technology. One goal is estimation of pain levels. A
second goal is automatic discrimination of real from faked pain.
NIH Grant 1R01NR013500-01A1
Development of a new technology for assessing pediatric pain (NTAP),
Bartlett, Huang (PIs).
Huang, Craig, Littlewort, Lee, Goodwin, Bartlett
Bartlett, M. (2015). Automated
facial expression analysis for pain assessment. American Pain
Society, Symposium on Improving Assessment of Clinical Pain Using Technology.
Palm Springs May 14.
Bartlett, M., Littlewort,
G., Frank, M., and Lee, K. (2014). Automated Detection of Deceptive Facial
Expressions of Pain. Current Biology 24(7) p. 738-743.
Link to
Journal.
Sikka, K., Dhall, A., and Bartlett,
M.S. (2014). Weakly Supervised Pain Localization and Classification with
Multiple Segment Learning. Image
and Vision Computing 32(10) p. 659-670. Download pdf
Sikka, K. Dahl, A., and Bartlett, M.S.
(2013). Weakly supervised pain localization using multiple
instance learning. Proc. IEEE International Conference
on Automatic Face and Gesture Recognition. P. 1-8. Best student paper honorable mention. Download pdf
Huang, J.,
Littlewort, G., and Bartlett, M. Automated facial
Expression Analysis for Measurement of Pain and Stress. University of
California Calit2 Strategic Research Opportunities Grant.
5/4/2010-5/2/2011.
Huang, J.,
Littlewort, G., and Bartlett, M. (2011). Use of computer vision technology to interpret clinical pain in children.
Poster presented at North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition. Oct 20-23,
Orlando, FL. Download pdf
Littlewort, Bartlett, & Lee (2009). Automatic coding of Facial Expressions displayed during
Posed and Genuine Pain. Image and Vision Computing, 27(12) p. 1741-1844. Download pdf
Littlewort,
G., Bartlett, M.S. and Lee, K., (2007). Automated measurement
of spontaneous facial expressions of genuine and posed pain. Proc. International Conference on Multimodal Interfaces, Nagoya,
Japan.
Download pdf
Littlewort,
G., Bartlett, M.S., and Lee, K. (2006). Faces of Pain: Automated measurement of
spontaneous facial expressions of genuine and posed pain. Proceedings of the
13th Joint Symposium on Neural Computation, San Diego, CA.
Abstract