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A Comparison between BCI Simulation and Neurofeedback for ForwardBackward Navigation in Virtual Reality
المؤلفون المشاركون
Alchalabi, Bilal
Faubert, Jocelyn
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-10-09
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
A brain-computer interface (BCI) decodes the brain signals representing a desire to do something and transforms those signals into a control command.
However, only a limited number of mental tasks have been previously investigated and classified.
This study aimed to investigate two motor imagery (MI) commands, moving forward and moving backward, using a small number of EEG channels, to be used in a neurofeedback context.
This study also aimed to simulate a BCI and investigate the offline classification between MI movements in forward and backward directions, using different features and classification methods.
Ten healthy people participated in a two-session (48 min each) experiment.
This experiment investigated neurofeedback of navigation in a virtual tunnel.
Each session consisted of 320 trials where subjects were asked to imagine themselves moving in the tunnel in a forward or backward motion after a randomly presented (forward versus backward) command on the screen.
Three electrodes were mounted bilaterally over the motor cortex.
Trials were conducted with feedback.
Data from session 1 were analyzed offline to train classifiers and to calculate thresholds for both tasks.
These thresholds were used to form control signals that were later used online in session 2 in neurofeedback training to trigger the virtual tunnel to move in the direction requested by the user’s brain signals.
After 96 min of training, the online band-power neurofeedback training achieved an average classification of 76%, while the offline BCI simulation using power spectral density asymmetrical ratio and AR-modeled band power as features, and using LDA and SVM as classifiers, achieved an average classification of 80%.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Alchalabi, Bilal& Faubert, Jocelyn. 2019. A Comparison between BCI Simulation and Neurofeedback for ForwardBackward Navigation in Virtual Reality. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1129395
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Alchalabi, Bilal& Faubert, Jocelyn. A Comparison between BCI Simulation and Neurofeedback for ForwardBackward Navigation in Virtual Reality. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1129395
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Alchalabi, Bilal& Faubert, Jocelyn. A Comparison between BCI Simulation and Neurofeedback for ForwardBackward Navigation in Virtual Reality. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1129395
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1129395
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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