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ArEEG_Words: Dataset for Envisioned Speech Recognition using EEG for Arabic Words by Darwish, Hazem; Malah, Abdalrahman Al; Jallad, Khloud Al; Ghneim, Nada is a scholarly article available to read on EtoBox.

What is ArEEG_Words: Dataset for Envisioned Speech Recognition using EEG for Arabic Words about?

Brain-Computer-Interface (BCI) aims to support communication-impaired patients by translating neural signals into speech. A notable research topic in BCI involves Electroencephalography (EEG) signals that measure the electrical activity in the brain. While significant advancements have been made in BCI EEG research, a major limitation still exists: the scarcity of publicly available EEG datasets for non-English languages, such as Arabic. To address this gap, we introduce in this paper ArEEG_Words dataset, a novel EEG dataset recorded from 22 participants with mean age of 22 years (5 female, 17 male) using a 14-channel Emotiv Epoc X device. The participants were asked to be free from any effects on their nervous system, such as coffee, alcohol, cigarettes, and so 8 hours before recording. They were asked to stay calm in a clam room during imagining one of the 16 Arabic Words for 10 seconds. The words include 16 commonly used words such as up, down, left, and right. A total of 352 EEG recordings were collected, then each recording was divided into multiple 250ms signals, resulting in a total of 15,360 EEG signals. To the best of our knowledge, ArEEG_Words data is the first of its kin

Author

Darwish, Hazem; Malah, Abdalrahman Al; Jallad, Khloud Al; Ghneim, Nada

Published

2024

Language

EN