Difference between revisions of "Biometric data capture (project)"
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| − | MFTi customized a biometric data acquisition system to facilitate experiments conducted with with industrial and university collaborators. Biometric data types acquired by | + | MFTi customized a biometric data acquisition system to facilitate experiments conducted with with industrial and university collaborators. Biometric data types acquired by our system included EDA, EEG, EMG, and pulse oximetry. The system was built using the ''bitAlino'' sensor interface platform; the ''OpenSignals'' data acquisition, processing, and visualization software system; and a custom optical sensing system to capture on-screen events. Eye tracking was performed using a separate Mirametrix system. MFTi developed custom software to process the data post acquisition, which included noise filtering, time-based synchronization of the biometric and eye tracking data, and statical analyses. Subsequent work within this project has focused on the evaluation of various emotion analysis technologies, including technologies based on facial analysis or biometric data analysis. |
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Revision as of 13:34, 11 April 2017
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Biometric data capture
The NBCC Mobile First Technology initiative (MFTi) has worked with various biometric data acquisition and emotion analysis technologies in support of proprietary projects.
Research topics
EDA, EEG, EMG, eye tracking, emotion detection, eye tracking, pulse oximetry, Affectiva, bitAlino, OpenSignals, Mirametrix
MFTi customized a biometric data acquisition system to facilitate experiments conducted with with industrial and university collaborators. Biometric data types acquired by our system included EDA, EEG, EMG, and pulse oximetry. The system was built using the bitAlino sensor interface platform; the OpenSignals data acquisition, processing, and visualization software system; and a custom optical sensing system to capture on-screen events. Eye tracking was performed using a separate Mirametrix system. MFTi developed custom software to process the data post acquisition, which included noise filtering, time-based synchronization of the biometric and eye tracking data, and statical analyses. Subsequent work within this project has focused on the evaluation of various emotion analysis technologies, including technologies based on facial analysis or biometric data analysis.
Project contact
William McIver Jr.
