EEG-SSVEP based Brain Machine Interface for Controlling of a Wheelchair and Home Appliances with Bluetooth Localization System
Authors: 
Isuru Ruhunage, Chamika Janith Perera, Induwara Munasinghe, Thilina Dulantha LalitharatneAuthors Info & Claims
Isuru Ruhunage, Chamika Janith Perera, Induwara Munasinghe, Thilina Dulantha LalitharatneAuthors Info & ClaimsPages 2520 - 2525
Abstract
Performing motor activities including activities of daily living (ADL) on their own is challenging for individuals who have lost their motor functionalities due to various conditions such as spinal cord injuries, cerebral palsy, spinal muscle atrophy etc. Their mobility is also restricted depending on the severity of the disability. This paper proposes an Electroencephalography (EEG) signals based brain machine interface (BMI) for a wheelchair along with the facility to control various home appliances depending on the location of the user. The proposed BMI uses Steady State Visual Evoked Potentials (SSVEP) of EEG signals to identify the user intentions and recognized intentions are used to control the wheelchair (by wheelchair controller) or operate different home appliance connected to the system (by home appliance controller) based on the location information estimated by a Bluetooth localization beacon system. A set of experiments were carried out with healthy subjects to validate the proposed system and the results yielded that the proposed BMI system has the ability to effectively control the wheelchair as well as different home appliances connected to system using only less number of user intention signals.
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Dec 2018
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IEEE Press
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Published: 12 December 2018
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