Facial Expressions as Behavioral Indicators for Assessing Pain using Machine Learning Models

Abstract

Pain is a symptom of a condition or disease. Pain experienced in the body is verbally reported to a health care giver. Currently there is no objective way to measure physical pain or discomfort one may be feeling. And so consequently, there is no way for caregivers to adequately assess patients in pain who cannot verbalize it, such as non-verbal, adult patients and young children. Facial expressions may be used as a behavioral indicator for evidence of pain which can then be used to communicate a patient's distress and pain severity. These facial expressions can be recognized through jaw clenching, eyebrow raising, and eye squinting. Machine learning with vision based algorithms may differentiate these behavioral face-indicators and assess the pain levels of nonverbal patients. There have emerged many vision based methods for predicting pain from face images. This review summarizes the development of pain recognition from facial expressive images or videos, datasets available for research, an overview of vision based methods using conventional and deep learning, the current challenges and limitations, and scope for improvement in future.