The understanding of surgical gesture, by means of measuring apparatus, can play a key role for a possible evaluation of the surgical performance and the human factors characterizing it. To this aim a neural network classification algorithm can be helpful, since combines good generalization performances along with a parsimonious architecture when dealing with high dimensional classification problems. So, here it is presented and proposed the development of an innovation in surgical training system, as a fundamental objective support for training of novice surgeons.
Gesture recognition and classification for surgical skill assessment / Saggio, G., Santosuosso, G.L., Cavallo, P., Pinto, C.a., Petrella, M., Giannini, F., Di Lorenzo, N., Lazzaro, A., Corona, A., D’Auria, F., Iezzi, L., Gaspari, A.. - (2011). (The 6th IEEE International Symposium on Medical Measurements and Applications (MeMeA 2011) Bari, Italy ) [10.1109/MeMeA.2011.5966681].
Gesture recognition and classification for surgical skill assessment
DI LORENZO, NICOLA;
2011
Abstract
The understanding of surgical gesture, by means of measuring apparatus, can play a key role for a possible evaluation of the surgical performance and the human factors characterizing it. To this aim a neural network classification algorithm can be helpful, since combines good generalization performances along with a parsimonious architecture when dealing with high dimensional classification problems. So, here it is presented and proposed the development of an innovation in surgical training system, as a fundamental objective support for training of novice surgeons.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
