Automated Assessment of Pain: Prospects, Progress, and a Path Forward

Advances in the understanding and control of pain require methods for measuring its presence, intensity, and other qualities. Shortcomings of the main method for evaluating pain-verbal report-have motivated the pursuit of other measures. Measurement of observable pain-related behaviors, such as facial expressions, has provided an alternative, but has seen limited application because available techniques are burdensome. Computer vision and machine learning techniques have been successfully applied to the assessment of painrelated facial expression, suggesting that automated assessment may be feasible. Further development is necessary before such techniques can have more widespread implementation in pain science and clinical practice. Suggestions are made for the dimensions that need to be addressed to facilitate such developments.