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
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر