Open AccessInvestigation of Hunger and Satiety Status During Eyes Open and Closed Using EEG Signals
Author(s) -
Egehan Çetin,
Gürkan Bilgin,
Süleyman Bilgin,
Yasemin Bıçer Gömceli,
Alparslan Melik Kayikci
Publication year - 2020
Publication title -
akıllı sistemler ve uygulamaları dergisi
Language(s) - English
Resource type - Journals
ISSN - 2667-6893
DOI - 10.54856/jiswa.202005105
Subject(s) - electroencephalography , brain–computer interface , context (archaeology) , computer science , wavelet , wearable computer , population , artificial intelligence , interface (matter) , pattern recognition (psychology) , psychology , medicine , neuroscience , embedded system , paleontology , environmental health , bubble , maximum bubble pressure method , parallel computing , biology
Surface EEG measurements that can be performed in hospitals and laboratories have reached a wearable and portable level with the development of today's technologies. Artificial intelligence-assisted brain-computer interface (BCI) systems play an important role in individuals with disabilities to process EEG signals and interact with the outside world. In particular, the research is becoming widespread to meet the basic needs of individuals in need of home care with an increasing population. In this study, it is aimed to design the BCI system that will detect the hunger and satiety status of the people on the computer platform through EEG measurements. In this context, a database was created by recording EEG signals with eyes open and eyes closed by 20 healthy participants in the first stage of the study. The noise of the EEG signal is eliminated by using a low pass, high pass, and notch filters. In the classification, using Wavelet Packet Transform (WPT) with Coiflet 1 and Daubechies 4 wavelets, 77.50% accuracy was achieved in eyes closed measurement, and 81% in eyes open measurement.