Abstract
Objective. We propose a combination of a constrained independent component analysis (cICA) with an ensemble empirical mode decomposition (EEMD) to analyze electroencephalographic recordings from depressed or schizophrenic subjects during olfactory stimulation. Approach. EEMD serves to extract intrinsic modes (IMFs) underlying the recorded EEG time. The latter then serve as reference signals to ...
Abstract
Objective. We propose a combination of a constrained independent component analysis (cICA) with an ensemble empirical mode decomposition (EEMD) to analyze electroencephalographic recordings from depressed or schizophrenic subjects during olfactory stimulation. Approach. EEMD serves to extract intrinsic modes (IMFs) underlying the recorded EEG time. The latter then serve as reference signals to extract the most similar underlying independent component within a constrained ICA. The extracted modes are further analyzed considering their power spectra. Main results. The analysis of the extracted modes reveals clear differences in the related power spectra between the disease characteristics of depressed and schizophrenic patients. Such differences appear in the high frequency gamma-band in the intrinsic modes, but also in much more detail in the low frequency range in the alpha-,theta- and delta-bands. Significance. The proposed method provides various means to discriminate both disease pictures in a clinical environment.
Altmetric