EEG-based Brain-computer Interface for Automating Home Appliances
نویسندگان
چکیده
منابع مشابه
EEG-based Brain-computer Interface for Automating Home Appliances
An EEG-based brain-computer system for automating home appliances is proposed in this study. Brain-computer interface (BCI) system provides direct pathway between human brain and external computing resources or external devices. The system translates thought into action without using muscles through a number of electrodes attached to the user’s scalp. The BCI technology can be used by disabled ...
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The paper presents the Brain-Computer Interface (BCI) based home control system. The proposed system isused to facilitate the handicapped and needy persons. Neurosky headset is used to detect Electroencephalogram (EEG) signal from brain activity. Recognizing the brain activity for certain thoughts and eye blinking patterns, we managed to correlate them with the switching and regulation of certa...
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Brain-Computer Interface (BCI) has added a new value to efforts being made under human machine interfaces. It has not only introduced new dimensions in machine control but the researchers round the globe are still exploring the possible uses of such applications. BCIs have given a hope where alternative communication channels can be created for the persons having severe motor disabilities. This...
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Movement-disabled persons typically require a long practice time to learn how to use a brain-computer interface (BCI). Our aim was to develop a BCI which tetraplegic subjects could control only in 30 minutes. Six such subjects (level of injury C4-C5) operated a 6-channel EEG BCI. The task was to move a circle from the centre of the computer screen to its right or left side by attempting visuall...
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Brain-Computer Interfaces (BCIs) are communication systems, which enable users to send commands to computers by using brain activity only; this activity being generally measured by Electroencephalography (EEG). BCIs are generally designed according to a pattern recognition approach, i.e., by extracting features from EEG signals, and by using a classifier to identify the user’s mental state from...
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ژورنال
عنوان ژورنال: Journal of Computers
سال: 2014
ISSN: 1796-203X
DOI: 10.4304/jcp.9.9.2159-2166