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Updated: Jun 5, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
Published on: September 8, 2023
Acquisition Of Balinese Imagined Spelling using Electroencephalogram (BISE) Dataset
I Made Agus Wirawan1, Ketut Paramarta2
1Data Science Lab, Engineering and Vocational Faculty, Universitas Pendidikan Ganesha, Udayana Street, No. 11 Singaraja, Bali, 81116, Indonesia.
Abstract:
One of the main goals of today's technology is to create a connected environment between humans and technological devices to perform daily physical activities. However, users with speech disorders cannot use this application. Loss of verbal communication can be caused by injuries and neurodegenerative diseases that affect motor production, speech articulation, and language comprehension. To overcome this problem, Brain-Computer Interfaces (BCI) use EEG signals as assistive technology to provide a new communication channel for individuals who cannot communicate due to loss of motor control. Of the several BCI studies that use EEG signals, no studies have studied Balinese characters. As a first step, this study examines the acquisition of EEG signal data for Balinese character recognition. There are several stages in obtaining EEG signal data for Balinese character spelling imagination in this study: preparation of research documents, preparation of stimulus media, submission of ethical permits, determination of participants, recording process, data presentation, and publication of datasets. The result datasets from this study are in the form of raw data, and data was analyzed for 18 Balinese and 6 vowel characters, both spelling and imagined.
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