S Sinigaglia
Scuola Superiore Sant'Anna, Ospedale Cisanello, University of Pisa
Papers
4
Total Citations
45
H-Index
4
About
S. Sinigaglia has made pioneering contributions to the field of surgical biomechanics and gesture analysis, fundamentally advancing how we understand and evaluate expertise in minimally invasive surgery (MIS). Their research focuses on developing objective metrics to assess surgeon performance, particularly during laparoscopy, where traditional training methods have struggled to keep pace with the technique's complexity. Sinigaglia's most cited work, "Using the Waseda Bioinstrumentation System WB-1R to analyze Surgeon’s performance during laparoscopy" (2007, 15 citations), introduced a global performance index that revolutionized how surgical skill is quantified. Building on this foundation, they developed a biomechanics–machine learning system for surgical gesture analysis (2013, 13 citations) and created a surgeon's musculo-skeletal model for proficiency assessment (2011, 11 citations). Their innovative use of Hidden Markov Models to decode surgical expertise (2006, 6 citations) provided unprecedented insights into the differences between novice and expert surgeons. Collectively, Sinigaglia's work has not only improved surgical training methodologies but also informed the design of next-generation robotic instruments, making a lasting impact on the safety and efficacy of modern surgical practice.
Research Focus
Key Achievements
Top Papers
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