The painful face: Pain expression recognition using active appearance models - Robotics Institute Carnegie Mellon University

The painful face: Pain expression recognition using active appearance models

A. B. Ashraf, Simon Lucey, T. Chen, K. Prkachin, P. Solomon, Zara Ambadar, and Jeffrey Cohn
Conference Paper, Proceedings of 9th International Conference on Multimodal Interfaces (ICMI '07), pp. 9 - 14, November, 2007

Abstract

Pain is typically assessed by patient self-report. Self-reported pain, however, is difficult to interpret and may be impaired or not even possible, as in young children or the severely ill. Behavioral scientists have identified reliable and valid facial indicators of pain. Until now they required manual measurement by highly skilled observers. We developed an approach that automatically recognizes acute pain. Adult patients with rotator cuff injury were video-recorded while a physiotherapist manipulated their affected and unaffected shoulder. Skilled observers rated pain expression from the video on a 5-point Likert-type scale. From these ratings, sequences were categorized as no-pain (rating of 0), pain (rating of 3, 4, or 5), and indeterminate (rating of 1 or 2). We explored machine learning approaches for pain-no pain classification. Active Appearance Models (AAM) were used to decouple shape and appearance parameters from the digitized face images. Support vector machines (SVM) were used with several representations from the AAM. Using a leave-one-out procedure, we achieved an equal error rate of 19% (hit rate = 81%) using canonical appearance and shape features. These findings suggest the feasibility of automatic pain detection from video.

BibTeX

@conference{Ashraf-2007-17048,
author = {A. B. Ashraf and Simon Lucey and T. Chen and K. Prkachin and P. Solomon and Zara Ambadar and Jeffrey Cohn},
title = {The painful face: Pain expression recognition using active appearance models},
booktitle = {Proceedings of 9th International Conference on Multimodal Interfaces (ICMI '07)},
year = {2007},
month = {November},
pages = {9 - 14},
}