PROJECT SUMMARY In light of the opioid crises, minimizing postoperative pain and postoperative opioid requirements to reduce chronic opioid dependency among surgical patients have become major concerns for surgeons and anesthesiologists. Effective intraoperative nociception control can mitigate these concerns. Unfortunately, existing nociceptive monitoring tools use indicators that are inherently susceptible to intraoperative influences. Monitoring these indicators often lead to suboptimal intraoperative opioid administration, since there is no way to account for whether these measures are being influenced by nociception or numerous other intraoperative factors such as blood loss, anesthetic drugs and antihypertensives. Therefore, improved methods to monitor surgical nociception are clearly needed. In short, currently available nociceptive monitors measure unreliable indicators and predispose surgical patients to suboptimal opioid dosing administration leading to ineffective intraoperative control. The consequences for surgical patients can be significant, since increased postoperative pain and opioid requirements is associated with increased incidence of opioid dependency. This project proposes to develop a state-of-the-art sensors, algorithms, and prospective observational data to construct an integrated measure of nociceptive control based on autonomic (EDA) and neurophysiologic markers of arousal and nociception (EEG-based arousal and opioid signatures).