Blar i NTNU Open på forfatter "Soler, Andres"
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Automated methodology for optimal selection of minimum electrode subsets for accurate EEG source estimation based on Genetic Algorithm optimization
Soler, Andres; Moctezuma, Luis Alfredo; Giraldo, Eduardo; Molinas, Marta (Peer reviewed; Journal article, 2022)High-density Electroencephalography (HD-EEG) has proven to be the EEG montage that estimates the neural activity inside the brain with highest accuracy. Multiple studies have reported the effect of electrode number on ... -
Automatic Detection of Mental Stress Responses from Electroencephalogram Signals
Sletten, Christian Moe (Master thesis, 2023)Denne avhandlingen presenterer en detaljert studie av effektiviteten og begrensningene av Elektroencefalografi (EEG)-basert psykisk stressdeteksjon hos mennesker ved bruk av en interpersonlig modell. Tre klassifiseringsalgoritmer, ... -
Automatic Sleep Stage Classification with Optimized Selection of EEG Channels
Stenwig, Håkon; Soler, Andres; Furuki, Junya; Suzuki, Yoko; Abe, Takashi; Molinas, Marta (Chapter, 2022)Visual inspection of Polysomnography (PSG) recordings by sleep experts, based on established guidelines, has been the gold standard in sleep stage classification. This approach is expensive, time-consuming, and mostly ... -
Classification of RGB Color Stimuli in Source Space
Fløtaker, Simen Piene (Master thesis, 2023)Denne oppgaven utforsker muligheten for å bruke elektroencefalografi (EEG) signaler for å avgjøre hvorvidt en person undergår rød, grønn, eller blå (RGB) visuelle stimuli. Dersom en algoritme kan utvikles, som kan klassifisere ... -
EEG source imaging of hand movement-related areas: An evaluation of the reconstruction accuracy with optimized channels
Soler, Andres; Giraldo, Eduardo; Molinas Cabrera, Maria Marta (Journal article; Peer reviewed, 2023)The hand motor activity can be identified and converted into commands for controlling machines through a brain-computer-interface (BCI) system. Electroencephalography (EEG) based BCI systems employ electrodes to measure ... -
EEG-Based Alcohol Detection System with AI Techniques: Towards the Design of BCI Systems for Driver Monitoring
Nordstrøm-Hauge, Iselin Johanna; Vassbotn, Molly (Master thesis, 2023)Denne masteroppgaven undersøker muligheten for å detektere tilstedeværelsen av alkohol i elektroencefalografi (EEG)-signaler. I dag er alkoholpåvirket kjøring et verdensomspennende problem. Målet med dette prosjektet er å ... -
EEG-Based Alcohol Detection System with AI Techniques: Towards the Design of BCI Systems for Driver Monitoring.
Nordstrøm-Hauge, Iselin Johanna; Vassbotn, Molly (Master thesis, 2023)Denne masteroppgaven undersøker muligheten for å detektere tilstedeværelsen av alkohol i elektroencefalografi (EEG)-signaler. I dag er alkoholpåvirket kjøring et verdensomspennende problem. Målet med dette prosjektet er å ... -
Low-density EEG Source Reconstruction: Towards an Automated Framework for Minimizing Electrode Count While Retaining High Accuracy
Soler, Andres (Doctoral theses at NTNU;2022:196, Doctoral thesis, 2022)In this thesis, multiple approaches for electroencephalographic (EEG) source reconstruction using low-density electrode counts are introduced. Source reconstruction provides valuable information about the location and ... -
Primary color decoding using deep learning on source reconstructed EEG signal responses
Fløtaker, Simen; Soler, Andres; Molinas Cabrera, Maria Marta (Peer reviewed; Journal article, 2023)The brain’s response to visual stimuli of different colors might be used in a brain-computer interface (BCI) paradigm, for letting a user control their surroundings by looking at specific colors. Allowing the user to control ... -
Psychological stress detection with optimally selected EEG channel using Machine Learning techniques
Marthinsen, Anne Jo; Galtung, Ivar; Cheema, Amandeep; Sletten, Christian; Andreassen, Ida Marie; Sletta, Øystein; Soler, Andres; Molinas Cabrera, Maria Marta (Peer reviewed; Journal article, 2023)Psychological stress buildup can lead to mental disorders, early mortality, stroke and sudden cardiac arrest and therefore, timely stress detection is important for reducing human suffering. This study aims to present a ... -
Relevance-based Channel Selection for EEG Source Reconstruction: An Approach to Identify Low-density Channel Subsets
Soler, Andres; Giraldo, Eduardo; Lundheim, Lars Magne; Molinas Cabrera, Maria Marta (Chapter, 2022)Abstract: Electroencephalography (EEG) Source Reconstruction is the estimation of the underlying neural activity at cortical areas. Currently, the most accurate estimations are done by combining the information registered ... -
The Augmented Human: Development of BCI for RGB colour-based automation
Buøen, Emma Horn; Ludvigsen, Sara Lund (Master thesis, 2021)Denne oppgaven undersøker muligheten for å klassifisere EEG signaler produsert av visuell eksponering av fargene rød, grønn og blå (RGB). Et datasett bestående av 31 subjekter ble analysert. Datasettet ble laget ved ... -
The Augmented Human: Development of BCI for RGB colour-based automation
Ludvigsen, Sara Lund; Buøen, Emma Horn (Master thesis, 2021)Denne oppgaven undersøker muligheten for å klassifisere EEG signaler produsert av visuell eksponering av fargene rød, grønn og blå (RGB). Et datasett bestående av 31 subjekter ble analysert. Datasettet ble laget ved ...