Project SPARS

Sequential Pattern Analysis in Robotic Surgery: Understanding Surgery

The objective of the SPARS project is to propose data analysis methods to better understand complex technical human activities, such as surgery. Surgery is a complex activity, that depends on many factors, including the patient and surgeon characteristics. Such complexity and variability explain why there is almost no detailed study of the surgical practice yet. Until now, the surgical procedure performed in the operating room is considered as a whole, as a black-box and is technically described with few words. Analysis usually consisted in comparing impact of different surgical approaches or of different pre-operative clinical patient’s parameters on post-operative outcomes. In the SPARS project, we will rely on a combination of data and model-driven approaches to analyze and compare kinematics of whole surgical procedures acquired during robotic assisted hysterectomies. The studied methods will be applied and validated on a unique data set of more than 60 surgeries with kinematics, annotated videos and clinical parameters of robotic assisted hysterectomies. We will demonstrate the clinical added value of the project by developing and evaluating a visualization software allowing to visualize and understand differences in practice between populations.



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