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SUMMARY:Practical non-invasive brain-machine interface system for communic
 ation and control
DTSTART:20130909T120000
DTEND:20130909T130000
DTSTAMP:20260410T034211Z
UID:242720fbebc3c9b467768192a48eeedce3ca0a61d08892434e02c8fd
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof Kenji Kansaku\, M.D.\, Ph.D.\, Department of Rehabilitat
 ion for Brain Functions\, Research Institute of National Rehabilitation C
 enter for Persons with Disabilities (Japan).\nThe Brain-Machine Interface 
 (BMI) or Brain–Computer Interface (BCI) is an interface technology that 
 utilizes neurophysiological signals from the brain to control external mac
 hines or computers (Birbaumer and Cohen\, 2007). We have developed EEG bas
 ed BMI systems for helping persons with physical disabilities. We first ap
 plied the P300 paradigm for communication and environmental control. We pr
 epared a green/blue flicker matrix\, and showed that the new matrix was as
 sociated with a better subjective feeling of comfort than was the conventi
 onal white/gray flicker matrix\, and we also found that the new matrix was
  associated with better performance (Takano\, et al.\, 2009). We further p
 roposed an advanced system by adding Augmented Reality (AR)\, in which we 
 applied an agent robot as a moving remote controller (Kansaku\, et al.\, 2
 010).\nFor clinical purposes\, we have developed an in-house environmental
  control system\, which consists of hardware (e.g.\, EEG amplifier) and so
 ftware. We also developed peripheral devices: a non-adhesive solid-gel EEG
  electrode (Toyama\, et al.\, 2012)\, a soft cap with electrode holders. T
 he P300 BMI system was successfully operated by patients with amyotrophic 
 lateral sclerosis (ALS) and cervical spinal cord injury (SCI) (Ikegami\, e
 t al.\, 2011).\nTo support arm and finger movements of quadriplegic patien
 ts\, we have developed in-house robotic exoskeletons\, and the steady-stat
 e visual evoked potential (SSVEP) paradigm was used for their asynchronous
  control. The system allowed cervical SCI patients to successfully perform
  reaching and grasping movements. We also developed a real-time MEG system
 \, which applies beamforming technique and imaginary coherence analysis\, 
 aiming to further develop new BMI and neurofeedback technologies (Ora\, et
  al.\, in press). Researches along these lines may help persons with disab
 ilities to expand the range of activities (Kansaku\, 2011).
LOCATION:SV1717a http://plan.epfl.ch/?room=SV%201717A
STATUS:CONFIRMED
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