| Yazarlar |
Peng Liu
|
Doç. Dr. İdris YAZGAN
Kastamonu Üniversitesi, Türkiye |
|
Sarah T Olsen
|
|
Alecia Moser
|
|
Umur Cifci
|
|
Saeed Bajwa
|
|
Tvetenstrand Christian
|
|
Peter Gerhadstein
|
|
Omowunmi Sadik
|
|
Lijun Yin
|
| Özet |
| 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. |
| Anahtar Kelimeler |
| Database | Expression analysis |
| Bildiri Türü | Tebliğ/Bildiri |
| Bildiri Alt Türü | Tam Metin Olarak Yayımlanan Tebliğ (Uluslararası Kongre/Sempozyum) |
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum |
| Bildiri Dili | İngilizce |
| Kongre Adı | 2018 13th IEEE International Conference on Automatic Face Gesture Recognition |
| Kongre Tarihi | 15-05-2018 / 19-05-2018 |
| Basıldığı Ülke | |
| Basıldığı Şehir |
| Atıf Sayıları | |
| SCOPUS | 3 |
