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Journal ArticleDOI

Controlling of smart home system based on brain-computer interface.

TLDR
The BCI and PoE technology, combined with smart home system, overcoming the shortcomings of traditional systems and achieving home applications management rely on EEG signal.
Abstract
Background Brain computer interface (BCI) technology is a communication and control approach. Up to now many studies have attempted to develop an EEG-based BCI system to improve the quality of life of people with severe disabilities, such as amyotrophic lateral sclerosis (ALS), paralysis, brain stroke and so on. The proposed BCIBSHS could help to provide a new way for supporting life of paralyzed people and elderly people. Objective The goal of this paper is to explore how to set up a cost-effective and safe-to-use online BCIBSHS to recognize multi-commands and control smart devices based on SSVEP. Methods The portable EEG acquisition device (Emotiv EPOC) was used to collect EEG signals. The raw signals were denoised by discrete wavelet transform (DWT) method, and then the canonical correlation analysis (CCA) method was used for feature extraction and classification. Another part is the control of smart home devices. The classification results of SSVEP can be translated into commands to control several devices for the smart home. Results Here, the Power over Ethernet (PoE) technology was utilized to provide electrical energy and communication for those devices. During online experiments, four different control commands have been achieved to control four smart home devices (lamp, web camera, guardianship telephone and intelligent blinds). Experimental results showed that the online BCIBSHS obtained 86.88 ± 5.30% average classification accuracy rate. Conclusion The BCI and PoE technology, combined with smart home system, overcoming the shortcomings of traditional systems and achieving home applications management rely on EEG signal. In this paper, we proposed an online steady-state visual evoked potential (SSVEP) based BCI system on controlling several smart home devices.

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Citations
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Journal ArticleDOI

Data Analytics in Steady-State Visual Evoked Potential-Based Brain–Computer Interface: A Review

TL;DR: The current research in SSVEP-based BCI is reviewed, focusing on the data analytics that enables continuous, accurate detection of SSVEPs and thus high information transfer rate, and the main technical challenges are described.
Journal ArticleDOI

Past, Present, and Future of EEG-Based BCI Applications

Kaido Värbu, +2 more
- 26 Apr 2022 - 
TL;DR: The objective of this review is to give a systematic overview of the literature on EEG-based BCI applications from the period of 2009 until 2019, and current challenges in the field and possibilities for the future have been analyzed.
Journal ArticleDOI

Channel Projection-Based CCA Target Identification Method for an SSVEP-Based BCI System of Quadrotor Helicopter Control.

TL;DR: The offline experimental results showed that the proposed channel projection-based canonical correlation analysis (CP-CCA) target identification method for steady-state visual evoked potential- (SSVEP-) based BCI system outperformed the CCA and the PSDA methods in terms of classification accuracy and information transfer rate (ITR).
Journal ArticleDOI

Facial expression recognition based on Electroencephalogram and facial landmark localization

TL;DR: A fusion facial expression recognition method based on EEG and facial landmark localization to improve the accuracy and generalization capability of Electroencephalogram (EEG) based facial expression Recognition.
Proceedings ArticleDOI

A BCI based Smart Home System Combined with Event-related Potentials and Speech Imagery Task

TL;DR: This study proposed a highly intuitive BCI paradigm that combines event-related potential (ERP) with the speech-imagery task for the individual target objects and the decoding accuracy of the proposed paradigm was 88.1% which is a much significant higher performance than a conventional ERP system.
References
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Relations Between Two Sets of Variates

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Evoked-Potential Correlates of Stimulus Uncertainty

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Journal ArticleDOI

Brain-computer interface technology: a review of the first international meeting

TL;DR: The first international meeting devoted to brain-computer interface research and development is summarized, which focuses on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users.
Journal ArticleDOI

A spelling device for the paralysed

TL;DR: A new means of communication for the completely paralysed that uses slow cortical potentials of the electro-encephalogram to drive an electronic spelling device is developed.
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