Application method of compressed sensing-based P300 brain-machine interface in smart home

Abstract

The invention discloses an application method of a compressed sensing-based P300 brain-machine interface in a smart home. The method includes: constructing a multi-source data collection and aggregation platform, wherein the platform includes a multi-function sensor and a displayer; collecting P300 EEG signals through EEG signal collection equipment, and compressing P300 EEG signals based on datacompressed-sensing theory to obtain observation signals; transmitting the observation signals in a wireless manner to a host computer through Wifi, then determining an estimation of sparse coefficients on the basis of an orthogonal matching tracking algorithm, and then reconstructing P300 EEG signals to use the same for subsequent analysis; and designing a P300 EEG signal-based ideation control platform to realize the ideation control of a target home appliance. According to the method, highly efficient acquisition of the P300 EEG signals can be realized on the basis of the compressed-sensingtheory, data transmission efficiency can be improved, EEG signals of a user can be converted into an effective control instruction, the brain-machine interface can be enabled to be effectively appliedin the smart home, and ideation control on the home appliance can be realized.

Description

technical field [0001] The invention relates to a brain-computer interface. In particular, it relates to an application method of a P300 brain-computer interface based on compressed sensing in smart homes. Background technique [0002] Brain-computer interface (BCI) is a channel for direct communication and control established between humans and external devices, enabling humans to transmit information to external devices without relying on nerves, muscles and other tissues around the brain. Commonly used paradigms in EEG experiments include Steady-State Visual Evoked Potential (SSVEP), P300, and motor imagery. Among them, P300 has the advantages of multiple classification categories and high accuracy, and is widely used in multi-classification experiments. [0003] Smart home is to connect all kinds of equipment terminals in the home environment through the home network. After integrating artificial intelligence and automation methods, the intelligentization of the home en...

AI Technical Summary

Problems solved by technology

However, at present, there are still problems in the connection between autonomous decision-making and human control in the smart home system.

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