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首页> 外文期刊>International Journal of Computer science and engineering Survey (IJCSES) >Brain Computer Interfaces Employing Machine Learning Methods : A Systematic Review
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Brain Computer Interfaces Employing Machine Learning Methods : A Systematic Review

机译:脑电脑接口采用机器学习方法:系统评价

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Research under the field of Brain Computer Interfaces is adapting various Machine Learning and Deep Learning techniques in recent times. With the advent of modern BCI, the data generated by various devices is now capable of detecting brain signals more accurately. This paper gives an overview of all the steps involved in the process of applying Machine Learning as well as Deep Learning methods from Data Acquisition to application of algorithms. It aims to study techniques currently employed to extract data, features from brain data, different algorithms employed to draw insights from the extracted features, and how it can be used in various BCI applications. By this study, I aim to put forward current Machine Learning and Deep Learning Trends in the field of BCI.
机译:脑电脑界面领域的研究正在调整各种机器学习和深度学习技术。随着现代BCI的出现,各种设备产生的数据现在能够更准确地检测大脑信号。本文概述了应用机器学习过程中涉及的所有步骤以及从数据采集到应用算法的应用程序。它旨在研究目前用于提取数据的技术,脑数据的特征,用于从提取的特征汲取洞察的不同算法,以及如何在各种BCI应用中使用它。通过这项研究,我的目标是提出了BCI领域的现行机器学习和深度学习趋势。

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