Towards Pain Monitoring: Facial Expression, Head Pose, a new Database, an Automatic System and Remaining Challenges

Abstract

Pain is what the patient says it is. But what about these who cannot utter? Automatic pain monitoring opens up prospects for better treatment, but accurate assessment of pain is challenging due to the subjective nature of pain. To facilitate advances, we contribute a new dataset, the BioVid Heat Pain Database which contains videos and physiological data of 90 persons subjected to well-defined pain stimuli of 4 intensities. We propose a fully automatic recognition system utilizing facial expression, head pose information and their dynamics. The approach is evaluated with the task of pain detection on the new dataset, also outlining open challenges for pain monitoring in general. Additionally, we analyze the relevance of head pose information for pain recognition and compare person-specific and general classification models.

Automatic Pain Recognition from Video and Biomedical Signals

“…• We improve the video-based system proposed by Werner et al [7] by reducing the level of noise in the extracted features (Sect. II).…”

“…Whereas some persons show strong facial reactions even for low stimulation, others show only little or no facial expression, also during high stimulation. More details on [7] are given below, as we advance this work in the present paper. The issue of pain posing is addressed by Littlewort et al [16].…”

“…All above mentioned works aim at predicting an observational measure, i. e. they employ computer vision and pattern recognition methods for analyzing facial expressions. Werner et al [7] go a step further and try to predict the pain stimulus that the person was subjected to.…”

“…For adequate pain management, the assessment must be repeated regularly, especially if the patient cannot call for help by himself. For providing a continuous assessment, we work towards an automatic system for measurement and monitoring of pain [7], [8], which can alert hospital staff timely and provide additional information for the patient's medical record. In this paper, we present first results in multi-modal pain recognition from video (i. e. facial expression, head movement) and biomedical signals (i. e. ECG, GSR, EMG).…”

FaceSync: Open source framework for recording facial expressions with head-mounted cameras

“…They commonly suffer data loss due to out-of-plane head motions and head rotations (Cohn & Sayette, 2010;Lucey et al, 2011;Werner et al, 2013) . Another common challenge pertains to the temporal precision in the temporal alignment of simultaneous recordings.…”