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Adverse events are the leading cause of morbidity and mortality in surgery, and approximately 40% of those events are judged to be preventable. Studies reviewing surgical adverse events found that cognitive factors such as cognitive workload and non-technical skills (e.g., situation awareness, communication, decision-making, and teamwork) contributed to more than half of the adverse events. To this end, it is critical to have a reliable, scalable, and easy-to-use technology that can assess the cognitive workload and non-technical skills of surgeons and surgical teams, so that the interventions/training can be designed accordingly to mitigate adverse events and hence improve patient safety. In this talk, she will discuss research to model cognitive workload and situation awareness (an essential component of non-technical skill) using wearable sensors and machine learning models. In the first part of the presentation, she will present an advanced real-time sensing paradigm that monitors the cognitive load of the surgeon and provides adaptive assistance as needed during robotic-assisted surgery. The second part of this talk will introduce a novel approach to assessing human situation awareness in natural scene viewing, as well as an illustration of how such techniques can be applied in complex surgical situations. The results of this study will enable real-time performance enhancement mechanisms, and guide practice/training for stakeholders across the healthcare organization.
Bio: Jing Yang is a Ph.D. candidate in the Department of Industrial Engineering at Purdue University. She received her master from the University of Michigan. She focuses on developing real-time systems for human cognitive functions and behavior modeling, as well as designing interventions to enhance human performance in a variety of environments. She was a recipient of the 2021 Human Factors Award for Excellence in Human Factors Research for innovation in designing cognitive workload-triggered adaptive automation for future robotic-assisted surgery.