Optic nerve simulation method and system based on deep learning

Abstract

The invention discloses an optic nerve simulation method and an optic nerve simulation system based on deep learning, wherein the method comprises the steps of transmitting a visible light signal; acquiring a visual neural electrical signal for obtaining a first visual neural simulated electrical signal, performing two-dimensional imaging on a brain visual processing cortex for obtaining a first near-infrared brain functional area simulated two-dimensional image; performing filtering, prior modification and sampling on the received visible light signal, and furthermore obtaining a second visual neural simulated electrical signal and a second near-infrared brain functional area simulated two-dimensional image; and performing analysis and evaluation, using data after evaluation as parameters for correcting a deep leaning module, and transmitting the data to the deep leaning module in a multi-dimensional vector form, thereby reconstructing a deep learning network by means of the multidirectional vector. According to the optic nerve simulation method, medical simulation and rehabilitation training can be performed on a human brain and an optic nerve system by means of a deep learning method. Simple operation and high reliability are realized. Furthermore along with increase of training data volume, system gain can be remarkably improved.

Description

technical field [0001] The invention relates to the technical field of computer artificial intelligence, in particular to a deep learning-based optic nerve simulation method and system. Background technique [0002] With the advancement of brain neuroscience and the development of artificial intelligence deep learning, as well as the rapid progress of neural signal processing technology, the use of artificial intelligence technology for brain-like computing and brain-computer interface realization has become a cross-field of computer science, medicine and life sciences. hotspot direction. It is possible to use electronic equipment and near-infrared equipment to collect EEG, active hotspots in brain regions, and muscle electrical signals. Through the collected muscle electrical signals, the information transmitted in the motor nerve can be analyzed, so as to realize the control of artificial muscles and exoskeleton machinery, or replace the motor nerve damaged by stroke and ...

AI Technical Summary

Problems solved by technology

Facts have proved that this method cannot converge in a limited search space, and as the amount of data increases, the computational complexity increases sharply, but the effect gain does not increase significantly, and there is even regression after training, which is far from being comparable to the human brain. performance on par with

Images