Yosrita, Efy and Heryadi, Yaya and Budiharto, Widodo (2020) Words classifier of imagined speech based on EEG for patients with disabilities. ICIC Express Letters, 14 (1). pp. 37-41. ISSN 1881803X
Full text not available from this repository.Abstract
Brain-Computer Interface (BCI) technology translates voluntary choices in
active command using brain activity. This work aims to interpret the EEG signals to
imagine the pronunciation of words without moving the articulatory muscles and without
uttering any audible sound (unspoken speech). Vocabulary consists of 4 words, namely
eat, drink, help and toilet. Each data recorded in 2 seconds using 14 channels EEG
from Emotiv device. We proposed the model and algorithm to classify the data from
the patients. Based on experiments using K-NN Classifier we got the average accuracy
95.3%; it is better than SVM (Support Vector Machine). This system should be used as
assistive technology for patients.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BCI, EEG, Unspoken speech, Emotiv, K-NN, SVM |
| Subjects: | Bidang Keilmuan > Algoritma Bidang Keilmuan > Analisis Spasial Bidang Keilmuan > Data Mining Bidang Keilmuan > Data Science Jurnal Bidang Keilmuan > Teknik Informatika |
| Divisions: | Fakultas Telematika Energi > S1 Teknik Informatika |
| Depositing User: | Yudha Formanto |
| Date Deposited: | 29 Oct 2025 04:11 |
| Last Modified: | 29 Oct 2025 04:11 |
| URI: | https://repository.itpln.ac.id/id/eprint/3100 |
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