Cognitive Avionics Toolset For Operator State Classifacation Based On Physiological Signals

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,...

Full description

Saved in:
Bibliographic Details
Main Author: Keller, B.M.
Format: Conference Proceeding
Language:English
Subjects:
Aerospace electronics
Aircraft
Cats
Electroencephalography
Galvanizing
Image sensors
Sampling methods
Skin
Temperature sensors
Thermal sensors
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2155-7195
2155-7209
DOI:10.1109/DASC.2007.4391951