Brain-computer Interaction in the Smart Era

Overview

Journal Curr Med Sci

Specialty General Medicine

Date 2024 Sep 30

PMID 39347924

Authors

Zi-Neng Yan

Peng-Ran Liu

Hong Zhou

Jia-Yao Zhang

Song-Xiang Liu

Yi Xie

Hong-Lin Wang

Jin-Bo Yu

Yu Zhou

Chang-Mao Ni

Li Huang

Zhe-Wei Ye

Affiliations

Soon will be listed here.

Abstract

The brain-computer interface (BCI) system serves as a critical link between external output devices and the human brain. A monitored object's mental state, sensory cognition, and even higher cognition are reflected in its electroencephalography (EEG) signal. Nevertheless, unprocessed EEG signals are frequently contaminated with a variety of artifacts, rendering the analysis and elimination of impurities from the collected EEG data exceedingly challenging, not to mention the manual adjustment thereof. Over the last few decades, the rapid advancement of artificial intelligence (AI) technology has contributed to the development of BCI technology. Algorithms derived from AI and machine learning have significantly enhanced the ability to analyze and process EEG electrical signals, thereby expanding the range of potential interactions between the human brain and computers. As a result, the present BCI technology with the help of AI can assist physicians in gaining a more comprehensive understanding of their patients' physical and psychological status, thereby contributing to improvements in their health and quality of life.

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