Smart home control method based on multi-mode brain-computer interface and augmented reality

Abstract

The invention discloses a smart home control method based on a multi-mode brain-computer interface and augmented reality. All modules are connected according to a sequence shown in figure 1, and a user normally wears an electroencephalogram signal collection cap and augmented reality equipment; a start button flickers at a fixed frequency, at the moment, an electroencephalogram signal processing module only carries out SSVEP signal detection on collected electroencephalograms of the user, if the user is watching the flickering button, a steady-state visual evoked potential SSVEP appears in the corresponding electroencephalogram collection cap, after the user enters a device menu main interface, operable smart home devices in an augmented reality knowledge base are arranged in a two-dimensional matrix form, and an improved P300 determinant stimulation normal form is adopted, so that the time efficiency during operation can be greatly improved when more targets need to be selected; multiple users can control smart home equipment in reality through the brain-computer interface and the augmented reality technology, and an access point is provided for the brain-computer interface in practical application.

Description

technical field [0001] The invention belongs to the technical field of smart home control, and in particular relates to a smart home control method based on a multimodal brain-computer interface and augmented reality. Background technique [0002] In today's society, with the continuous development of science and technology, people with disabilities or inconvenient activities also have some technological auxiliary equipment. How to better serve this group of people has become a direction of technological development. , conducted the following research and analysis: the inventions with application numbers 201711166187.2 and 201910524880.5 are control methods that combine SSVEP EEG signals with eye movement signals. The former uses the eye movement signal to select the controlled object in the interface displayed by the augmented reality device, and then uses the SSVEP EEG signal for further control; the latter directly fuses the eye movement signal and the SSVEP signal into t...

AI Technical Summary

Problems solved by technology

Generally, in the control method based on single-mode brain-computer interface, once there are many control instructions to be implemented, the system will either have low control efficiency or high error rate.

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