Miniaturized force-indentation depth sensor for tissue abnormality identification during laparoscopic surgery

Proceedings of: 2010 IEEE International Conference on Robotics and Automation (ICRA'10), May 3-8, 2010, Anchorage (Alaska, USA)This paper presents a novel miniaturized force-indentation depth (FID) sensor designed to conduct indentation on soft tissue during minimally invasive surgery. It can intra-operatively aid the surgeon to rapidly identify the tissue abnormalities within the tissue. The FID sensor can measure the indentation depth of a semi-spherical indenter and the tissue reaction force simultaneously. It make use of with fiber optical fiber sensing method measure indentation depth and force and is small enough to fit through a standard trocar port with a diameter of 11 mm. The created FID sensor was calibrated and tested on silicone block simulating soft tissue. The results show that the sensor can measure the indentation depth accurately and also the orientation of the sensor with respect to the tissue surface whilst performing indentation.European Community's Seventh Framework Progra

Pseudo-Haptics for Rigid Tool/Soft Object Interaction Feedback in Virtual Environments

This paper proposes a novel pseudo-haptics soft object stiffness simulation technique which is a marked improvement to currently used simulation methods and an effective low-cost alternative to expensive 3-DOF haptic devices. Soft object stiffness simulation is achieved by maneuvering an indenter avatar over the surface of a virtual soft object by means of an input device, such as a mouse, a joystick, or a touch-sensitive tablet. The alterations to the indenter avatar behavior produced by the proposed technique create for the user the illusion of interaction with a hard inclusion embedded in the soft object. The proposed pseudo-haptics technique is validated with a series of experiments conducted by employing three types of 2-DOF force-sensitive haptic surfaces, including a touchpad, a tablet with an S-pen input, and a tablet with a bare finger input. It is found that both the sensitivity and the positive predictive value of hard inclusion detection can be significantly improved by 33.3% and 13.9% respectively by employing tablet computers. Using tablet computers could produce results comparable to direct hand touch in detecting hard inclusions in a soft object. The experimental results presented here confirm the potential of the proposed technique for conveying haptic information in rigid tool / soft object interaction in virtual environments