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

Yükleniyor...
Küçük Resim

Tarih

2025

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

University of Kufa

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

Brain 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.

Açıklama

Anahtar Kelimeler

Attention level, BCI system, Electroencephalogram, Eye blink, Neurosky

Kaynak

Kufa Journal of Engineering

WoS Q DeÄŸeri

Scopus Q DeÄŸeri

Q4

Cilt

16

Sayı

3

Künye

Mohammed, 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