Design of a Training and Evaluation System for Surgical Robot Operation Based on Chai3d and LSTM Algorithm

Abstract

Compared with traditional surgery, femtosecond laser minimally invasive surgery has many uncomparable advantages and will have a significant impact on the medical industry in the future. In this paper, a simple scene for laser minimally invasive virtual surgery training is designed, in which the testers can practice repeatedly until the basic operational requirements are met. The haptic device adopts the Geomagic Touch from American 3D Systems Company. Eight testers using Geomagic Touch handle perform four basic actions (clamping, adjusting posture, pushing / pressing, moving tiny objects) in the left interface virtual environment. Each action was performed 10 times by per tester. During the process of human-computer interaction, the position, attitude, speed, button and other information of the handle are collected in real time, and the collected data is saved in the form of text. The collected data is multivariate time series data. Based on the characteristics of multivariate time series data, this paper proposes a design of an evaluation system based on LSTM model to classify the collected data and evaluate the standard of surgical action according to the output probability of action classification.