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S. Darvishi, Motor Imagery Performance Prediction Using a Reaction Time Test, 23rd July 2015.

  Abstract: Brain computer interfaces (BCIs) enable human brains to interact directly with machines. Motor imagery based BCI (MI-BCI) encodes the motor intentions of human agents and provides feedback accordingly. However, 15–30% of people are not able to perform vivid motor imagery. To save time and monetary resources, a number of predictors have been proposed […]

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Research Seminar 24th April – To feel or not to feel; that is the question

  Abstract: Brain-computer interfaces (BCI) have been used to enhance recovery after stroke. Different combinations of feedback modalities have been exploited in the application of BCI for stroke rehabilitation. Most studies have used visual only or a combination of visual and proprioceptive feedback. In this study we compare the performance of 10 healthy subjects on […]

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Research Seminar 22 August – Optimization of Brain-Computer Interfaces Design for Stroke Rehabilitation

The School of Electrical and Electronic Engineering invites you to the following Research Seminar: Optimization of Brain-Computer Interfaces Design for Stroke Rehabilitations Thursday, 22nd August 2013 4:10pm B19 Ingkarni Wardli Building (Where’s this?)   Abstract: Recently, the application of restorative brain-computer interfaces (BCIs) has received significant interest in many BCI labs. However, there are a […]

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