By Topic

An Artificial Neural Network approach for Haptic Discrimination in Minimally Invasive Surgery

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

7 Author(s)
Nicola Sgambelluri ; InterDept. Research Center "E. Piaggio", Faculty of Engineering, University of Pisa, Italy, via Diotisalvi, 2, 56126 Pisa, Italy ; Gaetano Valenza ; Marcello Ferro ; Giovanni Pioggia
more authors

In this paper we investigate the possibility of processing the tactile perception by using a novel biomimetic approach for the pattern recognition module. The goal is to enhance the perception in complex virtual environments deriving from haptic displays mimicking human tactile discrimination. To do this we explored a Minimally Invasive Surgery application where the tactile information are strictly limited. In fact, this promising technique suffers from some evident limitations due to the surgeon loss of tactile perception during palpation of internal organs. This is basically due to the mechanical transmission of the elongated tools used during operation. We propose to integrate an Artificial Neural Network in an electronic board capable of processing data provided by a sensorized laparoscopic tool. The capabilities of several pattern recognition techniques present in literature, the Principal Component Analysis (PCA), a Multilayer Perception (MLP) and a Kohonen Self-Organising Map (KSOM) are investigated. The results are compared with that obtained psychophysically on five viscoelastic materials.

Published in:

RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication

Date of Conference:

26-29 Aug. 2007