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Novel brain-computer interface method and system based on steady-state somatosensory evoked potential

An evoked potential, machine interface technology, applied in computer parts, mechanical mode conversion, electrical digital data processing, etc., can solve problems such as visual fatigue

Inactive Publication Date: 2017-03-15
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Compared with MI-BCI, these two types of visual BCIs have a faster response rate, but they need to actively control the eyeballs to respond to visual stimuli, which can easily cause visual fatigue

Method used

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  • Novel brain-computer interface method and system based on steady-state somatosensory evoked potential
  • Novel brain-computer interface method and system based on steady-state somatosensory evoked potential
  • Novel brain-computer interface method and system based on steady-state somatosensory evoked potential

Examples

Experimental program
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Effect test

Embodiment 1

[0033] A new brain-computer interface method based on steady-state somatosensory evoked potentials, see figure 1 , The brain-computer interface method includes the following steps:

[0034] 101: Place two ECG electrodes on the left and right wrists respectively, and perform electrical stimulation on the left and right hands respectively according to the preset frequency to induce slight tremor of the thumb and induce obvious steady-state somatosensory evoked potential;

[0035] 102: Use a four-period task mode to stimulate the subjects, collect EEG data, and perform preprocessing;

[0036] 103: Perform feature extraction and pattern recognition on the preprocessed EEG data through the co-space pattern algorithm, and obtain single-task EEG feature vectors of four frequency bands;

[0037] 104: Input the single-task EEG feature vectors of the four frequency bands into the support vector machine to train the classifier, and then predict the spatial features from the test set.

[0038] Amon...

Embodiment 2

[0046] The following describes the scheme in Embodiment 1 in detail with reference to specific drawings and calculation formulas. For details, see the following description:

[0047] 201: median nerve stimulation;

[0048] Among them, electrical stimulation is simultaneously applied to the bilateral median nerve through a bidirectional pulse with a pulse width of 200μs. Two ECG electrodes separated by 4 cm are placed on the left and right wrists respectively, such as figure 2 Shown. The left-hand stimulation frequency was 26 Hz, and the right-hand stimulation frequency was 31 Hz. The position of the electrodes on the left and right wrists and the magnitude of the current were adjusted to induce slight tremors in the thumb and induce obvious steady-state somatosensory evoked potentials. The current intensity of all subjects varied between 1.5-7mA.

[0049] Among them, the embodiment of the present invention does not limit the distance between the two ECG electrodes, and can be set...

Embodiment 3

[0074] The feasibility verification of the schemes in Examples 1 and 2 will be done below in conjunction with specific test data, as detailed in the following description:

[0075] Table 1 shows the classification accuracy of 14 subjects under the FBCSP algorithm. As can be seen from Table 1, the classification accuracy rate of the sixth subject was the highest, reaching over 93%. Among them, the seventh subject performed the worst, with an accuracy rate of less than 60%. The average classification accuracy rate of all subjects reached 70%.

[0076] The above results indicate that it is feasible to modulate the SSSEP induced by electrical stimulation by somatosensory selection and attention, and to establish a brain-computer interface system based on SSSEP.

[0077] Table 1. Classification accuracy rate of 14 subjects under FBCSP algorithm

[0078]

[0079] In summary, the SSSEP selective attention modulation method based on bilateral median nerve stimulation and the feature extract...

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Abstract

The invention discloses a novel brain-computer interface method and system based on steady-state somatosensory evoked potential. The method comprises the steps that two electrocardio-electrodes are put at the wrists of the left hand and the right hand respectively, electrical stimulation is simultaneously conducted on the left hand and the right hand according to preset frequency, thumbs are induced to produce slight tremble, and obvious steady-state somatosensory evoked potentials are induced; task modes in four stages are adopted to simulate a subject, and electroencephalogram data is acquired for preprocessing; feature extraction is conducted on the preprocessed electroencephalogram data by adopting a frequency-division-section co-space mode algorithm to obtain single-time task electroencephalogram feature vectors of four frequency bands, and further mode recognition is performed; the vectors are input into a support vector machine training classifier to predict spatial features from a test set. The problem that autonomous control of the eyes is lost is avoided, a large number of training is not needed, additional visual pathways are not also occupied, and corresponding feature extraction method is explored. In addition, the feasibility of the method and the system is verified through tests, and the multiple demands in actual application are met.

Description

Technical field [0001] The invention relates to the field of brain-computer interface systems, in particular to a novel brain-computer interface method and system based on steady-state somatosensory evoked potentials. Background technique [0002] The Brain-Computer Interface (Brain-Computer Interface) technology monitors and recognizes the human brain’s thought signal patterns through computers, and translates them into computer instructions, so that the human brain can directly carry out “thinking” without the participation of the motion system. -Information exchange between foreign objects. Motor imagery (MI), that is, there is only motor intention but no actual action output, which can cause changes in the activity state of a large number of neurons in the sensory motor area of ​​the cerebral cortex, and cause certain frequency components in the brain electrical signal to be attenuated or synchronized. Enhanced, this phenomenon is called event-related desynchronization or sy...

Claims

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Application Information

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IPC IPC(8): G06F3/01G06K9/62
CPCG06F3/015G06F18/2411
Inventor 明东奕伟波邱爽綦宏志杨佳佳
Owner TIANJIN UNIV
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