title: Algorithm based on the short-term Rényi entropy and IF estimation for noisy EEG signals analysis.
abstract: Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its time-frequency distribution (TFD) has been proposed in this paper. The algorithm utilizes the modification of the Rényi entropy-based technique for number of components estimation, called short-term Rényi entropy (STRE), and upgraded by an iterative algorithm which was shown to enhance existing approaches. Combined with instantaneous frequency (IF) estimation, the proposed method was applied to EEG signal analysis both in noise-free and noisy environments for limb movements EEG signals, and was shown to be an efficient technique providing spectral description of brain activities at each electrode location up to moderate additive noise levels. Furthermore, the obtained information concerning the number of EEG signal components and their IFs show potentials to enhance diagnostics and treatment of neurological disorders for patients with motor control illnesses.
authors.affiliation: University of Rijeka, Faculty of Engineering, Department of Computer Engineering, Vukovarska 58, HR-51000 Rijeka, Croatia. Electronic address: jlerga@riteh.hr.
authors.forename: Jonatan
authors.initials: J
authors.lastname: Lerga
authors.affiliation: University of Rijeka, Faculty of Engineering, Department of Automation and Electronics, Vukovarska 58, HR-51000 Rijeka, Croatia. Electronic address: nsaulig@riteh.hr.
authors.forename: Nicoletta
authors.initials: N
authors.lastname: Saulig
authors.affiliation: University of Rijeka, Faculty of Medicine, Ulica Brace Branchetta 20/1, HR-51000 Rijeka, Croatia. Electronic address: vladimir.mozetic@ri.t-com.hr.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Mozetič
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology; D004569:Electroencephalography / Q000379:methods*; D019277:Entropy; D005121:Extremities / Q000502:physiology; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio
keywords: EEG signals; Instantaneous frequency (IF) estimation; Rényi entropy; Short-term Rényi entropy (STRE); Time-frequency signal analysis