Brain-computer Interaction in the Smart Era

• Published in: Current medical science 2024-12, Vol.44 (6), p.1123-1131
• Main Authors: Yan, Zi-neng, Liu, Peng-ran, Zhou, Hong, Zhang, Jia-yao, Liu, Song-xiang, Xie, Yi, Wang, Hong-lin, Yu, Jin-bo, Zhou, Yu, Ni, Chang-mao, Huang, Li, Ye, Zhe-wei
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Artificial Intelligence in Medicine; Brain - physiology; Brain-Computer Interfaces; Electroencephalography - methods; Humans; Machine Learning; Medicine; Medicine & Public Health; Review
• ISSN: 2096-5230; 2523-899X; 2523-899X
• DOI: 10.1007/s11596-024-2927-6

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.