TY - GEN
T1 - Clinical valid pain database with biomarker and visual information for pain level analysis
AU - Liu, Peng
AU - Yazgan, Idris
AU - Olsen, Sarah
AU - Moser, Alecia
AU - Ciftci, Umur
AU - Bajwa, Saeed
AU - Tvetenstrand, Christian
AU - Gerhardstein, Peter
AU - Sadik, Omowunmi
AU - Yin, Lijun
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/5
Y1 - 2018/6/5
N2 - Pain is one of the most common and distressing symptoms reported by emergency room patients. Valid and reliable assessment of pain is essential for both clinical trials and effective pain management. A major limitation of automatic pain assessment by the facial expression is the lack of clinically validated data. This work aims at collecting a pain expression database for pain intensity analysis in clinical settings. The database includes 140 color video sequences, 140 multi-sensor sequences obtained by the Kinect 2, patients' sequence-level self-report, Cyclooxygenases (COXs) level, and inducible nitric oxide synthase (iNOS) level in the blood samples. The database also includes head poses and derived facial landmarks from the 2D video. The relationships of their self-report, Cyclooxygenases (COXs), inducible nitric oxide synthase (iNOS), head pose and facial expression are analyzed. The correlation between the clinical and non-clinical pain facial expressions have been evaluated as well.
AB - Pain is one of the most common and distressing symptoms reported by emergency room patients. Valid and reliable assessment of pain is essential for both clinical trials and effective pain management. A major limitation of automatic pain assessment by the facial expression is the lack of clinically validated data. This work aims at collecting a pain expression database for pain intensity analysis in clinical settings. The database includes 140 color video sequences, 140 multi-sensor sequences obtained by the Kinect 2, patients' sequence-level self-report, Cyclooxygenases (COXs) level, and inducible nitric oxide synthase (iNOS) level in the blood samples. The database also includes head poses and derived facial landmarks from the 2D video. The relationships of their self-report, Cyclooxygenases (COXs), inducible nitric oxide synthase (iNOS), head pose and facial expression are analyzed. The correlation between the clinical and non-clinical pain facial expressions have been evaluated as well.
KW - Database
KW - Expression analysis
UR - http://www.scopus.com/inward/record.url?scp=85049398723&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049398723&partnerID=8YFLogxK
U2 - 10.1109/FG.2018.00084
DO - 10.1109/FG.2018.00084
M3 - Conference contribution
AN - SCOPUS:85049398723
T3 - Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
SP - 525
EP - 529
BT - Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
Y2 - 15 May 2018 through 19 May 2018
ER -