Treffer 1 - 7 von 7 für Suche 'Blanco, Rosmary', Suchdauer: 0,58s Treffer weiter einschränken
  1. 1
    Comparing structure–function relationships in brain networks using EEG and fNIRS

    Comparing structure–function relationships in brain networks using EEG and fNIRS von Blanco, Rosmary, Preti, Maria Giulia, Koba, Cemal, Ville, Dimitri Van De, Crimi, Alessandro

    Veröffentlicht in Scientific reports

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  2. 2
    Investigating the interaction between EEG and fNIRS: A multimodal network analysis of brain connectivity

    Investigating the interaction between EEG and fNIRS: A multimodal network analysis of brain connectivity von Blanco, Rosmary, Koba, Cemal, Crimi, Alessandro


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  3. 3
    Resting State Brain Connectivity Analysis from EEG and FNIRS Signals

    Resting State Brain Connectivity Analysis from EEG and FNIRS Signals von Blanco, Rosmary, Koba, Cemal, Crimi, Alessandro


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  4. 4
    Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load

    Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load von Grzeszczyk, Michal K, Adamczyk, Paulina, Marek, Sylwia, Pręcikowski, Ryszard, Kuś, Maciej, Lelujko, M Patrycja, Blanco, Rosmary, Trzciński, Tomasz, Sitek, Arkadiusz, Malawski, Maciej, Lisowska, Aneta


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  5. 5
    Impact of the Pre-processing and Balancing of EEG Data on the Performance of Graph Neural Network for Epileptic Seizure Classification

    Impact of the Pre-processing and Balancing of EEG Data on the Performance of Graph Neural Network for Epileptic Seizure Classification von Mazurek, Szymon, Blanco, Rosmary, Falcó-Roget, Joan, Argasiński, Jan K., Crimi, Alessandro


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  6. 6
    Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load

    Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load von Grzeszczyk, Michal K, Adamczyk, Paulina, Marek, Sylwia, Pręcikowski, Ryszard, Kuś, Maciej, Lelujko, M. Patrycja, Blanco, Rosmary, Trzciński, Tomasz, Sitek, Arkadiusz, Malawski, Maciej, Lisowska, Aneta

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  7. 7
    Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load

    Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load von Grzeszczyk, Michal K, Adamczyk, Paulina, Marek, Sylwia, Pręcikowski, Ryszard, Kuś, Maciej, Lelujko, M Patrycja, Blanco, Rosmary, Trzciński, Tomasz, Sitek, Arkadiusz, Malawski, Maciej, Lisowska, Aneta

    Veröffentlicht in arXiv.org

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