  Pain is a complex and subjective experience that poses a number of
measurement challenges. While self-report by the patient is viewed as the gold
standard of pain assessment, this approach fails when patients cannot verbally
communicate pain intensity or lack normal mental abilities. Here, we present a
pain intensity measurement method based on physiological signals. Specifically,
we implement a multi-task learning approach based on neural networks that
accounts for individual differences in pain responses while still leveraging
data from across the population. We test our method in a dataset containing
multi-modal physiological responses to nociceptive pain.
