BCI-DRONE CONTROL BASED ON THE CONCENTRATION LEVEL AND EYE BLINK SIGNALS USING A NEUROSKY HEADSET

Basit Öğe Kaydı
dc.contributor.authorMohammed, Ali Abdulwahhab
dc.contributor.authorAbdulwahhab, Ali H.
dc.contributor.authorAbdulaal, Alaa Hussein
dc.contributor.authorMahmood, Musaria Karim
dc.contributor.authorMyderrizi, Indrit
dc.contributor.authorYassin, Riyam Ali
dc.contributor.authorAbdulridha, Taha Talib
dc.contributor.authorValizadeh, Morteza
dc.date.accessioned2025-08-21T12:18:39Z
dc.date.available2025-08-21T12:18:39Z
dc.date.issued2025
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalı
dc.description.abstractBrain neurons activate Human movements by producing electrical bio-signals. Neuron activity is used in several technologies by operating their applications based on mind waves. The Brain-Computer Interface (BCI) technology enables a processor to connect with the brain using a signal received from the brain. This study proposes a drone controlled using EEG signals acquired by a Neurosky device based on the BCI system. Two active signals are adapted for controlling the drone motions: concentration brain signals portrayed by attention level and the eye blinks as an integer value. A dynamic classification method is implemented via a Linear Regression algorithm for attention-level code. The eye blinking generates a binary code to control the drone's motions. The accuracy of this code is improved through Artificial Neural Networks and Machine Learning techniques. These codes (attention level and eye blink codes) drive two controlling layers and manipulate nine possible drone movements. The experiment was evaluated with several users and showed high performance for the classification methods and developed algorithm. The experiment shows a 90.37% accuracy control that outperforms most existing experiments. Also, the experiment can support 16 commands, making the algorithm appropriate for various applications.
dc.identifier.citationMohammed, A. A., Abdulwahhab, A. H., Abdulaal, A. H., Mahmood, M. K., Myderrizi, I., Yassin, R. A., ... & Valizadeh, M. (2025). BCI-DRONE CONTROL BASED ON THE CONCENTRATION LEVEL AND EYE BLINK SIGNALS USING A NEUROSKY HEADSET. Kufa Journal of Engineering, 16(3), 702-724. 10.30572/2018/KJE/160339
dc.identifier.doi10.30572/2018/KJE/160339
dc.identifier.endpage724
dc.identifier.issn2071-5528
dc.identifier.issue3
dc.identifier.scopus2-s2.0-105012896465
dc.identifier.scopusqualityQ4
dc.identifier.startpage702
dc.identifier.urihttps://hdl.handle.net/20.500.12939/5934
dc.identifier.volume16
dc.indekslendigikaynakScopus
dc.institutionauthorAbdulwahhab, Ali H.
dc.language.isoen
dc.publisherUniversity of Kufa
dc.relation.ispartofKufa Journal of Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Öğrenci
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAttention level
dc.subjectBCI system
dc.subjectElectroencephalogram
dc.subjectEye blink
dc.subjectNeurosky
dc.titleBCI-DRONE CONTROL BASED ON THE CONCENTRATION LEVEL AND EYE BLINK SIGNALS USING A NEUROSKY HEADSET
dc.typeArticle

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
Ä°sim:
Tam Metin / Full Text
Boyut:
931.45 KB
Biçim:
Adobe Portable Document Format
Ä°ndir
Lisans paketi
Listeleniyor 1 - 1 / 1
[ X ]
Ä°sim:
license.txt
Boyut:
1.17 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
Ä°ndir

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu