The under-assessment of pain response is one of the primary barriers to the adequate treatment of pain in critically ill patients and is associated with many negative outcomes such as chronic pain after discharge, prolonged mechanical ventilation, longer ICU stay and increased mortality risk.

Currently, existing nonverbal pain assessment scales are based on manual assessment by trained nurses of a patients’ facial expressions and the patients’ activity such as guarding or restlessness. Furthermore, manual pain assessment tools cannot monitor pain continuously and autonomously.

Rashidi and her team will equip two 24-bed ICU units with wearable inertial sensors and color-depth cameras. They will recruit 200 patients, and will capture highly-granular data on facial expressions and body movements for up to seven days.