A comprehensive dataset for home appliance control using ERP-based BCIs with the application of inter-subject transfer learning.

ABSTRACT: Brain-computer interfaces (BCIs) have a potential to revolutionize human-computer interaction by enabling direct links between the brain and computer systems. Recent studies are increasingly focusing on practical applications of BCIs-e.g., home appliance control just by thoughts. One of the non-invasive BCIs using electroencephalography (EEG) capitalizes on event-related potentials (ERPs) in response to target stimuli and have shown promise in controlling home appliance. In this paper, we present a comprehensive dataset of online ERP-based BCIs for controlling various home appliances in diverse stimulus presentation environments. We collected online BCI data from a total of 84 subjects among whom 60 subjects controlled three types of appliances (TV: 30, door lock: 15, and electric light: 1

SUBMITTER: Lee J 

PROVIDER: S-EPMC10867822 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature