Tag: Aslogic S.L

  • E-pilots Dataset

    E-pilots Dataset

    Pilot cognitive tasks must deal not only with a procedure, but also interleaving with different interruptions such as the controller instructions, the ECAM warnings and other emergent issues. One goal of E-PILOTS project is to evaluate the potential of cognitive computing flight deck supporting tools to preserve the situational awareness of the pilots while improving their performance in stressful flying scenarios.

    The aim of this study is to recognize several levels of workload from EEG and ECG sensors in different scenarios. For that we collected 4 different datasets: 2 with a serious games and 2 with flight simulator systems.

    Data from Serious Games

    Data from Simulators

    CITATION

    If you want to use this dataset in your research, please cite this database as:
    Hernández-Sabaté, A.; Yauri, J.; Folch, P.; Piera, M.À.; Gil, D. Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals. Appl. Sci. 2022, 12, 2298. https://doi.org/10.3390/app12052298

    PARTNERS

    Department of Telecommunications and Systems Engineering – UAB
    Aslogic S.L

    FUNDING

    This research is partially supported by the H2020 Clean Sky 2 project: “E-PILOT: Evolution of cockPIt operations Levering on cOgnitive compuTing Services” (Grant Agreement No. 831993)

  • Cognitive States Recognition

    Cognitive States Recognition

    Project Description

    When performing different tasks along the day, people experiment different levels of cognitive state depending on the level of attention required, the difficulty of such task and how many sub-tasks are needed to take care off.
    Physiological measures provide a more reliable data of cognitive state by measuring physiological dynamic changes which cannot be controlled consciously. Electroencephalogram (EEG) and electrocardiogram (ECG) are the preferred ones among researchers.
    The goal of this project is to characterize the cognitive state by means of neural networks from EEG and ECG signals.

    PARTNERS

    Department of Telecommunications and Systems Engineering – Universitat Autònoma de Barcelona (UAB), Aslogic S.L, Cranfield University

    FUNDING

    This project has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No 831993. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Clean Sky 2 JU members other than the Union.