In this paper we present a system for the evaluation of the skill of a physician or physician student by means of the analysis of the movements of the hand. By comparing these movements to the ones of a set of subjects known to be skilled, we could tell if they are correct. We consider the execution of a typical surgical task: the suture. For the data acquisition we used the HiTEg sensory glove, then, we extract a set of features from data analysis and classify it by means of different kind of classifiers. We compared results from an RBF neural network and a Bayesian classifier. The system has been tested on a set of 18 subjects. We found that accuracy depends on the feature set that is used, and it can reach 94% when we consider a set of 20 features: 9 of them are taken from data of bending sensor, 10 from accelerometers and gyroscopes, and one feature is the length of the gesture

Costantini, G., Saggio, G., Sbernini, L., DI LORENZO, N., Casali, D. (2015). Towards an Objective Tool for Evaluating the Surgical Skill. In J. Merelo (a cura di), Computational Intelligence (pp. 325-335). Springer International Publishing [10.1007/978-3-319-26393-9_19].

Towards an Objective Tool for Evaluating the Surgical Skill

COSTANTINI, GIOVANNI;SAGGIO, GIOVANNI;DI LORENZO, NICOLA;
2015-11-25

Abstract

In this paper we present a system for the evaluation of the skill of a physician or physician student by means of the analysis of the movements of the hand. By comparing these movements to the ones of a set of subjects known to be skilled, we could tell if they are correct. We consider the execution of a typical surgical task: the suture. For the data acquisition we used the HiTEg sensory glove, then, we extract a set of features from data analysis and classify it by means of different kind of classifiers. We compared results from an RBF neural network and a Bayesian classifier. The system has been tested on a set of 18 subjects. We found that accuracy depends on the feature set that is used, and it can reach 94% when we consider a set of 20 features: 9 of them are taken from data of bending sensor, 10 from accelerometers and gyroscopes, and one feature is the length of the gesture
25-nov-2015
Settore ING-INF/01 - ELETTRONICA
English
Rilevanza internazionale
Capitolo o saggio
Neural networks; data glove; hand-gesture; classification; surgery
http://link.springer.com/chapter/10.1007/978-3-319-26393-9_19
Surgical Skill Evaluation by Means of a Sensory Glove and a Neural Network
Costantini, G., Saggio, G., Sbernini, L., DI LORENZO, N., Casali, D. (2015). Towards an Objective Tool for Evaluating the Surgical Skill. In J. Merelo (a cura di), Computational Intelligence (pp. 325-335). Springer International Publishing [10.1007/978-3-319-26393-9_19].
Costantini, G; Saggio, G; Sbernini, L; DI LORENZO, N; Casali, D
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/132788
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