Pain Recognition Using Artificial Neural Network

Facial expressions are a key index of emotion. To make use of the information afforded by facial expression for emotion science and clinical practice, reliable, valid, and efficient methods of measurement are critical. Enabling computer systems to recognize facial expressions and infer emotions from them is a challenging research topic. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector and facial feature tracker for face detection and feature extraction respectively. The face detector uses skin color modeling approach. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to the artificial neural network which uses standard error backpropagation algorithm for classification of painful and painless faces