XU Minpeng, WANG Youliang, MEI Jie, WANG Kun, MING Dong. Review of Non-invasive Asynchronous Brain-computer Interface Technology[J]. JOURNAL OF SIGNAL PROCESSING, 2023, 39(8): 1386-1398. DOI: 10.16798/j.issn.1003-0530.2023.08.005
Citation: XU Minpeng, WANG Youliang, MEI Jie, WANG Kun, MING Dong. Review of Non-invasive Asynchronous Brain-computer Interface Technology[J]. JOURNAL OF SIGNAL PROCESSING, 2023, 39(8): 1386-1398. DOI: 10.16798/j.issn.1003-0530.2023.08.005

Review of Non-invasive Asynchronous Brain-computer Interface Technology

  • ‍ ‍The brain-computer interface provides the brain with an information pathway to directly control external devices, and can be divided into synchronous and asynchronous systems according to whether there is a synchronous trigger signal. Synchronous BCI sets a synchronous trigger signal to force the human brain to communicate synchronously with the computer, requiring the user to operate strictly in accordance with the synchronous signal sent by the computer, and constraining the user to follow a fixed rhythm output command, thus limiting the user’s autonomy in controlling external devices, which is difficult to meet Control requirements in practical application scenarios. Compared with the synchronous BCI system, the asynchronous BCI does not need to set a synchronous trigger signal, and can process and respond to EEG signals in real time. The asynchronous BCI enables the user to independently control the time for outputting instructions by detecting the user’s control state and idle state. Therefore, the asynchronous BCI system is completely controlled by the user, which is more natural and practical in terms of human-computer interaction. At present, the implementation methods of asynchronous BCI control state detection can be mainly divided into two categories, namely state switching switch detection and autonomous control state detection. The asynchronous BCI system based on the detection of the state switching switch connects the state switching switch with the BCI system to form a two-step hybrid system. When the user selects the set independent switch, a corresponding switch signal will be generated, and the asynchronous BCI realizes the switching of the control state of the system by detecting the switch signal. The asynchronous BCI system based on autonomous control state detection does not have an independent state switching switch, but directly decodes the collected EEG signals, and analyzes whether there is an effective component corresponding to the control signal, so as to realize state detection and switching. This paper summarizes the basic principles and key technologies of two asynchronous BCI systems, and discusses their future development trends, in order to promote the in-depth research, development and application of asynchronous BCI technology.
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