Needle biopsy is an important and a common procedure for lesion detection within human body, but is difficult to perform and train the surgeons due to the presence of many critical organs and lack of complete visualization. It is also known that the most experienced physicians conducting such procedures rely primarily on the sense of “touch” or “feel” of different organs inside the body to estimate the needle positions as compared to the visual-aid systems like ultrasound scans. In this work, we would like to focus on developing a Simulator for Biopsy Training  System for training surgeons or residents on virtual phantoms, based on visual and force feedback. Such a simulator can be used to train surgeons for planning the optimal path of a needle, practicing the procedure without risk and developing the sense of “touch”. Incorporating visual and haptic feedback in a surgical training simulator provides with capabilities to expand, assist, train and monitor surgical skills for improvement as in augmenting the manual precision and in scaling motions and forces as in dexterity.

In order to develop a virtual- haptic model of blue phantom, material testing experiments were conducted with needle puncturing different regions of a blue phantom (typically used in training of surgeons) and measuring the needle reaction forces using the force sensor. For this purpose, the needle was mounted on a 6 DOF robotic platform (hexapod) to move at constant velocities. The force-displacement data obtained was used to develop haptic models for the phantom based on several existing methods as discussed in the literature to calculate the force feedback for the haptic user interface (HUI) comprising of a haptic device, in this case, Quanser HD2 haptic device.

The haptic user interface (HUI) in general is used to denote the computer controlled electromechanical system (“haptic device”), the feedback control laws (“haptic control laws”) as well as all the intermediate elements (A/D, D/A, conditioning electronics) that help interface the motions and forces between the human operator and the virtual environment. The effectiveness of the interface – in communicating the human user intent to the virtual environment and rendering of the results back to the users – can be judged using performance benchmarks such as the fidelity, transparency, stability, accuracy and real-time interactivity.

Finally, the simulator will be tested by senior surgeons and residents for validation before actually deploying it into the training program. A series of experimental and subject studies will eventually be carried in order to quantify the fidelity of generated haptic models as well as their ability to transfer the skills from experts to trainee, thereby highlighting the issues and challenges that will be addressed in our future work.