Paper: The Painful Face – Pain Expression Recognition Using Active Appearance Models

Ahmed Bilal Ashraf, Simon Lucey, Jeffrey F. Cohn, Tsuhan Chen, Zara Ambadar, Kenneth M. Prkachin, and Patricia E. Solomon. 2009. The painful face - Pain expression recognition using active appearance models. Image Vision Comput. 27, 12 (November 2009), 1788-1796.

Self-reported pain is a big problem because it is difficult to interpret and may be impaired or not even possible, as in young children or the severely ill. The authors of this paper tackle this problem by developing a computer vision system that automatically recognizes acute pain.

To achieve their goal, adult patients with rotator cuff injury were video-recorded while a physiotherapist manipulated their affected and unaffected shoulder. 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). And a facial expresion detector were implemented, as can be seen in the figure below.

They got good results (figure below) and concluded that automatic pain detection through video appears to be a feasible task. This finding suggests an oppor- tunity to build interactive systems to detect pain in diverse populations, including infants and speech impaired adults. 

Also, two limitations were noted. One was the exclusion of subjects wearing glasses or having facial hair, which limits generalizability. A second limitation was the availability of ground-truth at the level of video recorded tests instead of the level of individual frames.

Future work:

- Additional applications for system development include pain-triggered automatic drug dispensation and discriminating between feigned and real pain.