Blar i NTNU Open på forfatter "Moctezuma, Luis Alfredo"
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Towards a minimal EEG channel array for a biometric system using resting-state and a genetic algorithm for channel selection
Moctezuma, Luis Alfredo; Molinas Cabrera, Maria Marta (Peer reviewed; Journal article, 2020)We present a new approach for a biometric system based on electroencephalographic (EEG) signals of resting-state, that can identify a subject and reject intruders with a minimal subset of EEG channels. To select features, ... -
Towards an API for EEG-Based Imagined Speech classification
Moctezuma, Luis Alfredo; Molinas Cabrera, Maria Marta (Chapter, 2018)In this paper, imagined speech classification is performed with an implementation in Python and using scikit-learn library, to create a toolbox intended for real-time classification. To this aim, the Discrete Wavelet ... -
Towards Universal EEG systems with minimum channel count based on Machine Learning and Computational Intelligence
Moctezuma, Luis Alfredo (Doctoral theses at NTNU;2021:7, Doctoral thesis, 2021)The aim of this thesis is to move one step forward towards the concept of electroencephalographic (EEG) systems that can achieve the same objectives as high-density EEG with a minimum required number of channels. This ... -
Two-dimensional CNN-based distinction of human emotions from EEG channels selected by Multi-Objective evolutionary algorithm
Moctezuma, Luis Alfredo; Abe, Takashi; Molinas Cabrera, Maria Marta (Peer reviewed; Journal article, 2022)In this study we explore how different levels of emotional intensity (Arousal) and pleasantness (Valence) are reflected in electroencephalographic (EEG) signals. We performed the experiments on EEG data of 32 subjects from ...