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SUMMARY:Considering user training and alternative applications to design U
 sable EEG-based BCI Technologies
DTSTART:20160322T103000
DTEND:20160322T113000
DTSTAMP:20260508T120252Z
UID:e369797a2e6d1f332cd1dcf1282491f651aeb01f75a233899b83dbe5
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Fabien Lotte\, Inria Bordeaux Sud-Ouest/LaBRI\nBio: Fabie
 n LOTTE obtained a M.Sc.\, a M.Eng. and a PhD degree in computer sciences\
 , all from the National Institute of Applied Sciences (INSA) Rennes\, Fran
 ce\, in 2005 and 2008 respectively. As a PhD candidate he was part of the 
 BUNRAKU team at the Inria Rennes Bretagne-Atlantique and member of the Ope
 nViBE project dedicated to brain-computer interfaces and virtual reality. 
 He was supervised by Dr. Anatole LECUYER and Pr. Bruno ARNALDI. His PhD Th
 esis received both the PhD Thesis award 2009 from AFRIF (French Associatio
 n for Pattern Recognition) and the PhD Thesis award 2009 accessit (2nd pri
 ze) from ASTI (French Association for Information Sciences and Technologie
 s).\nIn 2009 and 2010\, he was a research fellow at the Institute for Info
 comm Research (I2R) in Singapore\, working in the Brain-Computer Interface
  Laboratory led by Dr. Cuntai GUAN. Since January 2011\, he is a Research 
 Scientist (with tenure) at Inria Bordeaux Sud-Ouest\, France\, in team Pot
 ioc (http://team.inria.fr/potioc/). His research interests include brain-c
 omputer interfaces\, virtual reality and 3D interaction\, pattern recognit
 ion and signal processing.\nBrain-Computer Interfaces (BCIs) are systems t
 hat can translate brain activity patterns of a user - typically measured u
 sing Electroencephalography (EEG) - into messages or commands for an inter
 active application.\nAlthough EEG-based BCIs have proven promising for a w
 ide range of applications they are still scarcely used outside laboratorie
 s for practical applications. The main reason preventing EEG-based BCIs fr
 om being widely used is arguably their poor usability\, which is notably 
 due to their low reliability and long training times. A significant resear
 ch effort has been targeted at the EEG signal processing level to address 
 these issues.\nHowever\, in this talk I will present our work that aims a
 t making EEG-based BCIs usable\, i.e.\, at increasing their efficacy and e
 fficiency\, targeted at two other levels: \n1) at the user training level
 \, to ensure that users can learn to control a BCI efficiently and effect
 ively\, and\n2) at the usage level\, to explore novel applications of BCIs
  for which the current reliability can already be useful.\n   \nFirst\,
  we advocate that BCIs can be made more usable by guiding users to efficie
 ntly learn BCI control mastery. Indeed\, BCI control is known to be a skil
 l that needs to be learnt. A study of models and guidelines from education
 al sciences enabled us to identify many theoretical limitations of curren
 t standard BCI training approaches\, thus highlighting the need for altern
 ative ones. In particular\, educational sciences recommend to train people
  with adapted and adaptive training tasks\, using explanatory feedback in
  motivating environments. In contrast standard BCI training protocols are 
 commonly fixed\, repetitive\, rather boring and provide purely corrective 
 feedback. To address these limitations\, we studied what kind of users ma
 nage to use a BCI and why. We also explored new feedback types\, e.g.\, mu
 lti-user feedback and tactile feedback to help users to learn BCI control 
 skills more efficiently.\n   \nSecond\, BCIs can be made more usable by
  being used for other applications than communication and control. To this
  end\, we notably explored the use of BCIs for neuroergonomics\, i.e.\, us
 ing brain signals to passively estimate some of the relevant user's menta
 l states during human-computer interaction\, in order to assess the ergono
 mic qualities of this interface. In particular\, we showed that one can es
 timate mental workload during complex 3D manipulation and navigation\ntask
 s in order to assess or compare interaction techniques and devices. We hav
 e also been able to study stereoscopic displays by estimating visual comfo
 rt in EEG signals. Another usage of BCIs\, that we found promising and use
 ful\, is real-time brain activity and mental state visualization. We desi
 gned a number of devices based on augmented reality and/or tangible interf
 aces to enable novice users to visualize their own brain activity or menta
 l states in real-time\, with potential applications in fields as wide and
  diverse as education\, self-awareness or well-being.
LOCATION:H4 3 133.084 	 http://plan.epfl.ch/?lang=en&room=H4+3+133.084+%09
STATUS:CONFIRMED
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