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Usability and Performance Measure of a Consumer-grade Brain Computer Interface System for Environmental Control by Neurological Patients

Farzin, Deravi, Chee Siang, Ang, M A, Hannan Bin Azhar, Areej, Al-Wabil, Malcolm, Philips, Mohamed, Sakel (2015) Usability and Performance Measure of a Consumer-grade Brain Computer Interface System for Environmental Control by Neurological Patients. International Journal of Engineering and Technology Innovation, 5 (3). pp. 165-177. ISSN 2223-5329. E-ISSN 2226-809X. (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:56301)

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With the increasing incidence and prevalence of chronic brain injury patients and the current financial constraints in healthcare budgets, there is a need for a more intelligent way to realise the current practice of neuro-rehabilitation service provision. Brain-computer Interface (BCI) systems have the potential to address this issue to a certain extent only if carefully designed research can demonstrate that these systems are accurate, safe, cost-effective, are able to increase patient/carer satisfaction and enhance their quality of life. Therefore, one of the objectives of the proposed study was to examine whether participants (patients with brain injury and a sample of reference population) were able to use a low cost BCI system (Emotiv EPOC) to interact with a computer and to communicate via spelling words. Patients participated in the study did not have prior experience in using BCI headsets so as to measure the user experience in the first-exposure to BCI training. To measure emotional arousal of participants we used an ElectroDermal Activity Sensor (Qsensor by Affectiva). For the signal processing and feature extraction of imagery controls the Cognitive Suite of Emotiv's Control Panel was used. Our study reports the key findings based on data obtained from a group of patients and a sample reference population and presents the implications for the design and development of a BCI system for communication and control. The study also evaluates the performance of the system when used practically in context of an acute clinical environment.

Item Type: Article
Uncontrolled keywords: stroke, rehabilitation, brain-computer interface, electroencephalography, emotiv EPOC
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.P3 Pattern recognition systems
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Farzin Deravi
Date Deposited: 14 Jul 2016 15:03 UTC
Last Modified: 16 Feb 2021 13:36 UTC
Resource URI: (The current URI for this page, for reference purposes)
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