Join us for a guest presentation by Algelia Burton, a PhD Student in Human Factors Engineering!
Abstract:
Laparoscopic surgery poses significant ergonomic risks for surgeons, with high rates of musculoskeletal disorders (MSDs) linked to repetitive movements, static postures, and prolonged operative durations. Existing assessment tools鈥攊ncluding self-reported surveys, observational scoring systems (e.g., RULA), electromyography (EMG), and inertial measurement units (IMUs)鈥攑rovide useful data but are limited by recall bias, episodic measurement, and lack of real-time feedback. This research project investigates the integration of artificial intelligence (AI) and video-based posture capture to create a continuous, non-invasive ergonomic monitoring system. Using computer vision platforms such as OpenPose and MediaPipe, the system aims to detect improper posture in real time, alert surgeons, and facilitate immediate corrective behavior. The study will evaluate the accuracy, feasibility, and utility of this AI-based framework during laparoscopic procedures, with a focus on upper-body postures and joint angles. The anticipated outcomes include improved real-time ergonomic feedback, reduction in cumulative musculoskeletal strain, and enhancement of surgeon performance and longevity. Findings are expected to inform the development of technology-driven interventions, bridging the gap between ergonomic research and practical, actionable solutions in the operating room. By combining objective physiological measurements with AI-driven posture detection, this project contributes to the advancement of surgical education, occupational health, and workflow optimization in laparoscopic surgery.
We hope to inspire students to learn about biomedical engineering and to meet new students from around campus!