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S. Sinigaglia

Researcher at Sant'Anna School of Advanced Studies

Publications -  11
Citations -  202

S. Sinigaglia is an academic researcher from Sant'Anna School of Advanced Studies. The author has contributed to research in topics: Hidden Markov model & Airway. The author has an hindex of 7, co-authored 10 publications receiving 188 citations.

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Journal ArticleDOI

Modelling and Evaluation of Surgical Performance Using Hidden Markov Models

TL;DR: A method for defining a model of surgical expertise and an objective metric to evaluate performance in laparoscopic surgery is proposed based on the processing of kinematic data describing movements of surgical instruments.
Proceedings Article

A biomechanical analysis of surgeon's gesture in a laparoscopic virtual scenario.

TL;DR: Estimation of some biomechanical parameters enables to assess the abilities of surgeons and to distinguish an expert surgeon from a novice, in a laparoscopic virtual environment.
Proceedings ArticleDOI

Using the Waseda Bioinstrumentation System WB-1R to analyze Surgeon’s performance during laparoscopy - towards the development of a global performance index -

TL;DR: The WB-1R (or, better, a newer version tailored specifically for use in the operating room) could provide important additional information to help assess the experience and performance of surgeons, thus leading to the development of a global performance index for surgeons during MIS.
Journal ArticleDOI

Biomechanics-machine learning system for surgical gesture analysis and development of technologies for minimal access surgery.

TL;DR: Preliminary tests have confirmed the efficacy of the system for surgical gesture analysis, providing an objective evaluation of progress during training of surgeons in their acquisition of proficiency in MAS approach and highlighting useful information for the design and evaluation of master–slave manipulator systems.
Journal ArticleDOI

Proficiency assessment of gesture analysis in laparoscopy by means of the surgeon's musculo-skeleton model.

TL;DR: The model provides data on the evaluation of biomechanical parameters of surgical gesture not only in kinematic terms but also includes analysis of the dynamics of muscle contraction analysis during surgical manipulations.