Facial Expression Analysis for Estimating Pain in Clinical Settings

Pain assessment is vital for effective pain management in clinical settings. It is generally obtained via patient's self-report or observer's assessment. Both of these approaches suffer from several drawbacks such as unavailability of self-report, idiosyncratic use and observer bias. This work aims at developing automated machine learning based approaches for estimating pain in clinical settings. We propose to use facial expression information to accomplish current goals since previous studies have demonstrated consistency between facial behavior and experienced pain. Moreover, with recent advances in computer vision it is possible to design algorithms for identifying spontaneous expressions such as pain in more naturalistic conditions.