Matching pursuit algorithm for enhancing EEG signal quality and increasing the accuracy and efficiency of emotion recognition.

Matching pursuit algorithm for enhancing EEG signal quality and increasing the accuracy and efficiency of emotion recognition. Biomed Tech (Berl). 2020 Apr 01;: Authors: Momennezhad A Abstract In this paper, we suggest an efficient, accurate and user-friendly brain-computer interface (BCI) system for recognizing and distinguishing different emotion states. For this, we used a multimodal dataset entitled "MAHOB-HCI" which can be freely reached through an email request. This research is based on electroencephalogram (EEG) signals carrying emotions and excludes other physiological features, as it finds EEG signals more reliable to extract deep and true emotions compared to other physiological features. EEG signals comprise low information and signal-to-noise ratios (SNRs); so it is a huge challenge for proposing a robust and dependable emotion recognition algorithm. For this, we utilized a new method, based on the matching pursuit (MP) algorithm, to resolve this imperfection. We applied the MP algorithm for increasing the quality and SNRs of the original signals. In order to have a signal of high quality, we created a new dictionary including 5-scale Gabor atoms with 5000 atoms. For feature extraction, we used a 9-scale wavelet algorithm. A 32-electrode configuration was used for signal collection, but we used just eight electrodes out of that; therefore, our method is highly user-friendly and convenient for users. In order to evaluate ...
Source: Biomedizinische Technik/Biomedical Engineering - Category: Biomedical Engineering Tags: Biomed Tech (Berl) Source Type: research