KNX-based Lighting System Controlled by Brain Signals (EEG)

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.

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Publication Details

Published
2024-11-12
DOI
https://doi.org/10.1109/ls2463127.2024.10881370
Citations
1
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
0.28
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article

KNX-based Lighting System Controlled by Brain Signals (EEG)

Georges Zissis, Mohamad Hamady, Laurent Canale, Zouhour Araoud et al.
1 citations
Impact of Light on Environment and Health
0.28
article

KNX-based Lighting System Controlled by Brain Signals (EEG)

Georges Zissis, Mohamad Hamady, Laurent Canale, Zouhour Araoud, Sadeq Salim Alsaffar
article en
1 citations

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.

Centre National de la Recherche Scientifique (FR), University of Monastir (TN), Université Fédérale de Toulouse Midi-Pyrénées (FR), Institut National Polytechnique de Toulouse (FR), Arts, Sciences and Technology University in Lebanon (LB), Laboratoire Plasma et Conversion d'Energie (FR), École Nationale Supérieure d'Électrotechnique, d'Électronique, d'Informatique, d'Hydraulique et des Télécommunications (FR), Ecole Nationale d'Ingénieurs de Monastir
Affordable and clean energy
Openalex Percentile: Top 39%
Impact of Light on Environment and Health
0.28
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KNX-based Lighting System Controlled by Brain Signals (EEG) — Georges Zissis, Mohamad Hamady, et al. · (2024) | TGRS Research Map | TGRS