University of Bahrain
Scientific Journals

Versatile Brain-Computer-Interface for Severely-Disabled People

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dc.contributor.author Masaad, Sarah
dc.contributor.author Jassim, Safiya
dc.contributor.author Mahdi, Layla
dc.contributor.author Bahri, Zouhir
dc.date.accessioned 2020-07-21T16:44:56Z
dc.date.available 2020-07-21T16:44:56Z
dc.date.issued 2020-07-01
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/4043
dc.description.abstract A versatile Brain Computer Interface (BCI) system is designed and implemented to help severely disabled people achieve a fair level of autonomy. The proposed BCI is versatile in the sense it can flexibly be custom-tailored to individual users while not only mitigating deleterious artefacts, but also putting them to an advantage for an asynchronous, interactive, real-time, and fault-tolerant assistive system. It integrates, in a novel way, Independent Component Analysis (ICA) and correlation-based Template Matching (TM) in order to detect and intelligently deal with the artefacts. Hence, this BCI differentiates between involuntary eye blinks (considered artefacts, hence removed) and deliberate rapid eye blinks (considered synchronizing signals) used for distress calling, start/stop signalling, as well as fault-tolerance owing to the confirmation/cancellation of commands before their execution. Two classes of brain activities, optimized to suit the capabilities of each patient, are used to navigate through a flexible menu of commands intended to individually meet the users’ needs. The Wavelet Transform (WT) is used to extract sub-band-power-based features that are input to a Neural Network used as the classifier with a success rate reaching 90%. The system can flexibly be adapted to suit various scenarios involving binary load control (on/off of TV, light, A/C, etc…) as well as multilevel control (up/down level of bed, TV volume, room temperature…etc.). The merits of this system have been successfully demonstrated in practice, showing its potential contribution to smart hospitals and patient-care facilities. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Brain Computer Interface (BCI), Independent Component Analysis (ICA), Artefact Mitigation, EEG Signals, Wavelet Transform (WT), Neural Network (NN). en_US
dc.title Versatile Brain-Computer-Interface for Severely-Disabled People en_US
dc.type Article en_US
dc.volume 10 en_US
dc.pagestart 2 en_US
dc.pageend 10 en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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