Research result:
1. Definition and classification of brain-computer interface technology
According to the different ways of acquiring brain activity signals, it can be divided into two types of signal acquisition strategies: invasive and non-invasive. Invasive signal acquisition can acquire spatiotemporal signals and has a tremendous ability to distinguish patients' multidimensional intentions through implantation in the cerebral cortex. However, due to safety and ethical issues, the use of non-invasive brain-computer interface technologies based on collecting brain signals such as EEG, magnetoencephalography, functional near-infrared spectroscopy, or functional magnetic resonance imaging may be more practical than invasive brain-computer interface techniques. Technology is more promising.
EEG-based brain-computer interface technology can collect and use patients' neural signals as input signals, and provide real-time feedback so that patients can intuitively understand their brain activities, and at the same time control external devices such as computers or robots during rehabilitation training , without relying on residual muscle control. In clinical applications, such technologies are divided into auxiliary brain-computer interfaces and rehabilitation brain-computer interfaces according to different therapeutic effects.
2. The application of different modes of EEG brain-computer interface technology in the upper limb rehabilitation of stroke patients
EEG-based brain-computer interface technology is considered as a potential tool to promote the recovery of upper limb motor function after stroke. According to the mode of brain signal generation, it is generally divided into the form of EEG signals based on motor imagination and the form of EEG signals based on exercise attempts. Both forms of EEG signals can be identified, and then used to trigger and drive the external connection of the brain-computer interface. Devices such as functional electrical stimulation or exoskeleton robots form a complete closed-loop brain-computer interface system. Motor imagery can be defined as the rehearsal of movements, mental activity without any external physical movement, and is a complex cognitive operation that is produced by the patient himself. Motor attempts, in which patients move their hemiplegic hand as best they can, even when they have completely lost voluntary movement, have also been used in brain-computer interface technology after stroke.
Some researchers believe that motor attempts are more informative than motor imagery, because patients must actively inhibit limb movement during motor imagery, while patients behave more naturally during motor attempts. In the literature retrieved this time, there is no comparison of the training effects of the brain-computer interface technology based on the above two forms of EEG signals, so there is no clear conclusion on whether there is a difference in the training effects between the two.
3. Control of external devices by EEG-based brain-computer interface technology
The brain-computer interface is a system that records and decodes brain signals, and finally translates the neurophysiological signals related to the movement process acquired by the brain-computer interface system into instructions that the computer can recognize in real time, and uses these signals to control external devices. Create new feedback links between limb movements without the involvement of peripheral nerves and muscles. Although external brain-computer interface devices with different types of feedback, such as virtual reality technology, functional electrical stimulation, and exoskeleton robots, have shown great potential in the rehabilitation of upper limb functions in stroke patients, their curative effect observations are still a topic of current research. hotspots.
(1) Virtual reality technology improves patient participation and enthusiasm by providing a rich feedback environment, providing individuals with an immersive virtual reality stimulating environment, allowing individuals to be more involved in the virtual environment and have a stronger sense of immersive experience Through virtual reality technology, patients can better control the brain-computer interface system and improve the effect of brain-computer interface rehabilitation training.
(2) The functional electrical stimulation system not only promotes the somatosensory feedback of the distal muscle stimulation of the limbs, but also can correctly identify the patient's movement intention, and issue instructions to control the functional electrical stimulation equipment to complete the predetermined stimulation, and finally restore the motor function of the limbs and hand grip.
(3) On the one hand, the exoskeleton robot can perform certain specific actions according to the set program to complete the activities that the patient has lost. On the other hand, the exoskeleton robot mediated by the brain-computer interface can guide the patient's paralyzed limbs to perform through EEG feedback. Its expected activities, and these activities can also feedback and stimulate the damaged neural network to promote the connection of the corresponding functional areas of the central nervous system.
