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EEG-based communication system for patients with locked-in syndrome using fuzzy logic
Published in Institute of Electrical and Electronics Engineers (IEEE)
2017
Volume: 2017-January
   
Pages: 1 - 5
Abstract
Patients who are conscious and aware of their environment but are physically disabled are known to have Locked-in Syndrome. The causes for this medical condition include traffic accidents, drug addiction and brain clots. There are some available solutions nowadays to help them communicate but the down side is the requirement for physical training which can be both time and money consuming. The main objective of this project is to help these patients communicate and engage more effectively in their daily life. In this paper, an Electroencephalogram (EEG)-based communication system is developed to facilitate communication of these patients with their caretakers. The implementation is composed of both hardware and software. The hardware consists of a 14-channels EEG module and a tablet. The software parts are: processing algorithm, online database and an android application. The EEG module on the patients' scalps keeps reading brainwaves continuously. Meanwhile, the tablet in front of them displays six basic needs, namely, food, water, washroom, help, sleep and entrainment. When the patients focus on a specific need, it will be detected when it matches with a predefined reference in the processing algorithm. The processing is done using fuzzy logic pattern recognition based on eye movement and color detection. The database acts as a two-way communication link between the patients and their caretaker. As the message will be sent through it to the android application-which is installed in the caretakers' phones-in the form of a pop-up notification. Interchangeably, a response message can be sent by the caretakers to state they are on their way for instance. Besides, the tablet will generate a voice message to inform the people around the patients about their need. A prototype system has been developed and successfully tested. © 2017 IEEE.
About the journal
JournalData powered by TypesetBMEiCON 2017 - 10th Biomedical Engineering International Conference
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers (IEEE)
Open AccessNo
Concepts (4)
  •  related image
    EEG
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    Fuzzy logic
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    Pattern recognition
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    Online database