Year: 2024
Type: conference-paper
Abstract: This paper presents an assistive system for controlling different light sources throw brain signals. The aim is to improve home automation systems specially the lighting systems by developing an interface to integrate the KNX-based lighting systems with brain signals. The proposed system consists of three parts. The first part is for detecting the EEG signals from the brain cortex. The second part is the heart of our research which represents a gateway that receives the detected EEG signals, analyses them, generates appropriate KNX commands, and sends these commands to the final part of the proposed system which is the Lighting System (LS) that implemented using KNX protocol. After testing the proposed system against different persons, the results showed the system correctly response to the user actions from 68 to 80 % of the total issued signals, according to the brain headset used, hardware processing resources that implement the gateway and the environment factors that effect of the brain signals.
Institutions: Arts, Sciences and Technology University in Lebanon, University of Sciences and Arts in Lebanon, Centre National de la Recherche Scientifique, Institut National Polytechnique de Toulouse, Laboratoire Plasma et Conversion d'Energie, University of Monastir, Ecole Nationale d'Ingénieurs de Monastir, École Nationale Supérieure d'Électrotechnique, d'Électronique, d'Informatique, d'Hydraulique et des Télécommunications
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4406351902