Analysis of EEG Features to Control Multiple Devices - Rashid, Mamunur; Norizam, Sulaiman; Mahfuzah, Mustafa; M. S., Jadin; M. S., Najib (Universiti Malaysia Pahang, 2018)
Brain-Computer Interface (BCI) or Human-Machine Interface (HMI) now becoming vital engineering and technology field which applying EEG technologies to provide Assistive Technology (AT) to humans. This paper presents the analysis of EEG signals from various human cognitive or mental states to determine the suitable EEG features that can be employed to control multiple devices. Here, EEG features in term of average of power spectrum, standard deviation of power spectrum and spectral centroid of power spectrum are selected to recognize human mental or cognitive state from 3 difference exercises; i) solving math problem, ii) Playing game and iii) do nothing (relax). We have calculated average power spectrum, average standard deviation of power spectrum and average spectral centroid of power spectrum of alpha and beta band for three mental exercises.