基于稳定扩散模型的脑机交互建模

Discrete and Continuous Models and Applied Computational Science Pub Date : 2023-09-12 DOI:10.22363/2658-4670-2023-31-3-273-281

Eugeny Yu. Shchetinin

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引用次数: 0

摘要

本文研究了基于生成式深度学习稳定扩散模型的脑机交互(BCI)神经技术。提出了一种脑机接口建模算法，并描述了该算法在人工数据上的训练和测试。研究结果鼓舞了研究人员，并可用于脑机接口的各个领域，如远程学习、远程医疗和类人机器人的创建等。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Brain-computer interaction modeling based on the stable diffusion model

This paper investigates neurotechnologies for developing brain-computer interaction (BCI) based on the generative deep learning Stable Diffusion model. An algorithm for modeling BCI is proposed and its training and testing on artificial data is described. The results are encouraging researchers and can be used in various areas of BCI, such as distance learning, remote medicine and the creation of robotic humanoids, etc.

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来源期刊

Discrete and Continuous Models and Applied Computational Science

CiteScore

0.60

自引率

0.00%

发文量

审稿时长

10 weeks