Bionic-EyE: Evaluation of Eye Bottom Surgical Skill by Multi-Sensing

Abstract

This research proposed the measurement system of quantitative indices for evaluation of surgical skills during simulation of inner limiting membrane (ILM) peeling, one of the most complicated inner eye surgeries, on Bionic-EyE. This system consists of the 6DOF IMU attached to the forceps to monitor extra hand tremor and the artificial eye module embedded with the quartz crystal resonator (QCR) force sensor to measure tiny contact force of the forceps applied to the retinal model on the eye bottom during simulation. To extract hand tremor element from the accelerometer, we adapted extended Kalman filter to estimate posture of the forceps and remove gravitational acceleration at sampling rate of 10 ms. Using this system during ILM peeling simulation by an ophthalmologist, we succeeded in obtaining features of forceps motions quantitatively due to high resolution of the QCR force sensor and the posture estimation method.