Cheap signal connector In the past 20 years, the brain computer interface (BCI) has rapidly become a research and application hotspot. Since Vidal first introduced the term brain-computer interface in 1973, brain-computer interfaces have received increasing attention in the fields of Neuroscience, neuroengineering, and clinical rehabilitation. The original goal of brain-computer interface research was to provide a non-muscle-controlled information exchange channel to help people with severe motor impairments communicate with the outside world. Methods for monitoring brain activity, such as Electroencephalography, magnetoencephalography, functional magnetic resonance imaging, near-infrared spectroscopy functional imaging, and neuronal recording, can provide input signals to the brain-computer interface. Among all methods, electro-encephalogram (EEG) has become the most commonly used signal for brain -computer interface research because of its non-invasive, easy-to-use, and low-cost equip A typical brain-computer interface system consists of three parts: signal acquisition, signal processing, and device control (Figure 1). This article focuses only on non-invasive brain-computer interface methods based on EEG.
The brain-computer interface research pioneers laid an important foundation for the brain-computer interface field in the early work of the 20th century. In 1977, Vidal developed a brain-computer interface system based on visual event-related potentials (ERPs), which The 1988, Farwell and Donchin proposed and designed the P300 speller, which arranged characters into a 6×6 character matrix. The characters in the matrix were randomly flashed In the early 1990s, a brain-computer interface based on sensory motor rhythms emerged. Woplaw and other training users self-adjust the amplitude of the mu rhythm, and realize the one-dimensional control of The cursor by the change of the mu rhythm amplitude. Pfurtscheller et al. constructed an event-related desynchronization (ERD) brain-computer interface system based on sensory motion rhythm, Which distinguishes the left/right hand movement from the temporal and spatial modes of ERD. At the same time, the brain-computer interface paradigm based on event-related potential has been further extended. In 1992, Sutter developed a brain response interface based on Pseudo-random sequence modulation of visual evoked potentials (VEPs), which uses visual evoked potentials to identify the direction of user gaze on an 8x8 visual keyboard. In 1999, Birbaumer et al. used the amplitude changes of slow cortical potentials (SCPs) to Control the one-dimensional movement of the cursor, and realized a text-spelling brain-computer interface called the thinking translation device (TTD).
In the nearly 20 years after the 21st century, brain-computer interface research has developed rapidly, and the number of institutions involved in brain-computer interface research and related research publication has increased greatly. This is evidenced by the number of peer-reviewed papers In this field since 2000.