DocumentCode :
2256284
Title :
Cognitive Avionics Toolset For Operator State Classifacation Based On Physiological Signals
Author :
Keller, B. Michael
Author_Institution :
Univ. of Iowa, Iowa City
fYear :
2007
fDate :
21-25 Oct. 2007
Abstract :
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. This paper describes our solution to the data collection and analysis problem. We developed a software package called the cognitive avionics toolset (CATS). CATS facilitates multi-sensory operator state research.
Keywords :
artificial intelligence; avionics; electrocardiography; electroencephalography; infrared imaging; EEG; cognitive avionics toolset; data management; data sensors; electrocardiogram; eye tracking; galvanic skin response; operator state classifacation; physiological signals; pulse oximetry; respiration rate; skin temperature; thermal imaging; Aerospace electronics; Aircraft; Cats; Electroencephalography; Galvanizing; Image sensors; Sampling methods; Skin; Temperature sensors; Thermal sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Avionics Systems Conference, 2007. DASC '07. IEEE/AIAA 26th
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-1108-5
Electronic_ISBN :
978-1-4244-1108-5
Type :
conf
DOI :
10.1109/DASC.2007.4391951
Filename :
4391951
Link To Document :
بازگشت