Portal: A user-friendly environment for BCI models training

Anatoly Bobe, Grigory Rashkov, M. Komarova, Dmitry Fastovets
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Abstract

This paper describes an application dedicated to noninvasive electroencephalography (EEG) signal processing and recognition. The goal of the designed software is to provide endto-end support for brain-computer interface (BCI) routines including data acquisition, signal filtering and preprocessing, feature extraction, classification and subject feedback. The software is supplied with a large number of data processing tools including ready-to-use machine learning and deep learning techniques. The real-time processing mode is also implemented.
门户:用于BCI模型训练的用户友好的环境
本文介绍了一种用于无创脑电图(EEG)信号处理和识别的应用。所设计的软件的目标是为脑机接口(BCI)程序提供端到端支持,包括数据采集、信号滤波和预处理、特征提取、分类和受试者反馈。该软件提供了大量的数据处理工具,包括即用型机器学习和深度学习技术。实现了实时处理模式。
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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