As we entered the field of airborne cognitive avionics, we quickly realized the data management challenges the field presents. We employ large number of data sensors including 128-channel EEG, electrocardiogram (EKG), galvanic skin response (GSR), pulse oximetry, skin temperature, respiration rate, thermal imaging and eye tracking. The sensors produce data at varying sampling rates and must be synchronized with each and with the aircraft state. Further, the sheer volume of data created (tens of gigabytes per run) creates analysis challenges of its own.


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    Title :

    Cognitive Avionics Toolset For Operator State Classifacation Based On Physiological Signals


    Contributors:


    Publication date :

    2007-10-01


    Size :

    4892150 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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