Authors
Teena Hassan, Dominik Seuß, Johannes Wollenberg, Katharina Weitz, Miriam Kunz, Stefan Lautenbacher, Jens-Uwe Garbas, Ute Schmid
Publication date
2019/12/8
Source
IEEE transactions on pattern analysis and machine intelligence
Volume
43
Issue
6
Pages
1815-1831
Publisher
IEEE
Description
Pain sensation is essential for survival, since it draws attention to physical threat to the body. Pain assessment is usually done through self-reports. However, self-assessment of pain is not available in the case of noncommunicative patients, and therefore, observer reports should be relied upon. Observer reports of pain could be prone to errors due to subjective biases of observers. Moreover, continuous monitoring by humans is impractical. Therefore, automatic pain detection technology could be deployed to assist human caregivers and complement their service, thereby improving the quality of pain management, especially for noncommunicative patients. Facial expressions are a reliable indicator of pain, and are used in all observer-based pain assessment tools. Following the advancements in automatic facial expression analysis, computer vision researchers have tried to use this technology for developing …
Total citations
20202021202220232024612242025
Scholar articles
T Hassan, D Seuß, J Wollenberg, K Weitz, M Kunz… - IEEE transactions on pattern analysis and machine …, 2019