  Bedside caregivers assess infants' pain at constant intervals by observing
specific behavioral and physiological signs of pain. This standard has two main
limitations. The first limitation is the intermittent assessment of pain, which
might lead to missing pain when the infants are left unattended. Second, it is
inconsistent since it depends on the observer's subjective judgment and differs
between observers. The intermittent and inconsistent assessment can induce poor
treatment and, therefore, cause serious long-term consequences. To mitigate
these limitations, the current standard can be augmented by an automated system
that monitors infants continuously and provides quantitative and consistent
assessment of pain. Several automated methods have been introduced to assess
infants' pain automatically based on analysis of behavioral or physiological
pain indicators. This paper comprehensively reviews the automated approaches
(i.e., approaches to feature extraction) for analyzing infants' pain and the
current efforts in automatic pain recognition. In addition, it reviews the
databases available to the research community and discusses the current
limitations of the automated pain assessment.
