A Hybrid Brain Computer Interface Based on Electroencephalography and Functional Transcranial Doppler Ultrasound

#Brain #Computer #Interface #BCI #EEG #fTCD #Electroencephalography #Functional #Transcranial #Doppler #Ultrasound
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Hybrid brain computer interfaces (BCIs) combining multiple brain imaging modalities have been proposed recently to boost the performance of single modality BCIs. We advance the state of hybrid BCIs by introducing a novel system that measures electrical brain activity as well as cerebral blood flow velocity using Electroencephalography (EEG) and functional transcranial Doppler ultrasound (fTCD), respectively. The system we developed employs two different paradigms to induce changes simultaneously in EEG and fTCD and to infer user intent. One of these paradigms include visual stimuli to simultaneously induce steady state visually evoked potentials (SSVEPs) and instruct users to perform word generation (WG) and mental rotation (MR) tasks, while the other paradigm instructs users to perform left and right arm motor imagery (MI) tasks through visual stimuli. A fixation cross that resembles baseline was introduced in both paradigms. This talk describes the methods used to evaluate the performance of both paradigms, and the results of the comparison.

 


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  • Date: 20 Nov 2019
  • Time: 06:30 PM to 08:00 PM
  • All times are (GMT-05:00) US/Eastern
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  • 3700 O'Hara Street
  • Pittsburgh, Pennsylvania
  • United States
  • Building: Benedum Hall
  • Room Number: 1235
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  • Co-sponsored by Co-sponsored by CH02079 - Pittsburgh Section Jt Chapter (SP01/CS23) and CH02142 - Pittsburgh Section Chapter (EMB18)
  • Starts 20 October 2019 09:00 PM
  • Ends 20 November 2019 01:00 PM
  • All times are (GMT-05:00) US/Eastern
  • 6 in-person spaces left!
  • No Admission Charge
  • Menu: Meat, No Meat

  Speakers

Dr. Murat Akcakaya Dr. Murat Akcakaya of Electrical and Computer Engineering Department, University of Pittsburgh

Biography:

Murat Akcakaya received his B.Sc. in Electrical and Electronics Engineering from Middle East Technical University in Ankara, Turkey, in 2005, and his M.Sc. and the Ph.D degrees in Electrical Engineering from Washington University in St. Louis, in May and December 2010, respectively. He is currently an Assistant Professor in the Electrical and Computer Engineering Department of the University of Pittsburgh. His research interests include statistical signal processing and machine learning with applications to noninvasive electroencephalography (EEG) based brain-computer interface (BCI) systems, array signal processing, and physiological signal analysis for health informatics. He is an NSF 2019 CAREER award recipient. He has more than 100 publications in leading journals and conferences.  He was the winner of the student paper contest awards at the 2010 IEEE Radar Conference; the 2010 IEEE Waveform Diversity and Design Conference; and the 2010 Asilomar Conference on Signals, Systems and Computers.