Pain Intensity Estimation from Mobile Video Using 2D and 3D Facial Keypoints

For the more than 300 million surgeries performed worldwide every year, managing post-surgical pain is critical for successful surgical outcomes. Pain is the most prominent post-surgical concern, with an estimated 86% of surgical patients in the United States experiencing pain after surgery, with 75% of these patients reporting at least moderate to extreme pain [1]. Higher postoperative pain is associated with more postoperative complications [2], indicating the importance of pain management. Furthermore, the use of opioid analgesics is a powerful tool for managing pain but can pose risks of adverse drug events (experienced by 10% of surgical patients), leading to prolonged length of stay, high hospitalization costs, and potentially addiction [3]. Thus, regular and careful pain assessment is important for balancing between pain relief and potential side effects of powerful opioid analgesics [4]. However, one of the challenges of pain management is accurately assessing the pain level of patients. Pain is inherently subjective, and the personal experience of pain is difficult to observe and measure objectively by those not experiencing it [5] (e.g., care providers). The standard practice used in clinical care requires patients to self-report their pain intensity level using a numeric or visual scale, such as the popular Numerical Pain Rating Scale [6].