IIST BCI Dataset-9: EEG Dataset For Malayalam Vocal and Subvocal Commands with Dialect Variation For Wheelchair Control

We developed IIST BCI Dataset-9, a novel EEG-based Brain-Computer Interface (BCI)dataset to improve wheelchair control systems using Malayalam dialect variations. BCIsystems help people with motor disabilities by allowing them to control devices using brainsignals. The limited number of BCI datasets in Indian languages makes it harder for nativespeakers to use these systems. To address this, we created a dataset with 15 Malayalamwords related to basic wheelchair commands like Forward, Backward, Go, Stop, Reverse,Right, and Left. The volunteer pronounced these words vocally and subvocally, eachrepeated 10 times. Non-invasive Electroencephalography (EEG) sensors were employed tocapture the brain activity associated with these tasks. Data was collected from volunteersacross 10 districts of Kerala to include different language variations. This dataset can helpimprove machine learning and BCI systems by making them more accurate anduser-friendly. It also supports the development of assistive technologies forMalayalam-speaking individuals with neurological conditions.