A Multi-device Intelligent Collaborative Training Method Based on Respiratory Motion Phase Determination

Abstract

This invention provides a multi-instrument intelligent collaborative training method based on respiratory motion phase determination, comprising the following steps: constructing a three-dimensional virtual anatomical model including the urethra, bladder, ureter, and kidney, and establishing an interactive connection between the force feedback handle of the simulated surgical instrument and the three-dimensional virtual anatomical model; selecting respiratory samples from a preset database and sending them to the three-dimensional virtual anatomical model, which then simulates the changes in other organs and tissues during lung respiration; collecting kidney motion data from the three-dimensional virtual anatomical model and dividing the kidney motion phase based on the motion data; generating instruction commands based on the kidney motion phase and the surgical instrument, and visually displaying the instruction commands; and having the user perform simulated training through the force feedback handle according to the instruction commands, with reinforcement learning used to optimize the training movements. By introducing kidney motion changes caused by lung respiration, the method can simulate real surgical situations and improve training effectiveness.

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