A brain computer interface (BCI) allows a person to communicate with external devices using electroencephalogram (EEG) or other brain signals. A typical BCI scheme consists of data acquisition, feature extraction and classification. Using the classifier output, a control command is issued to the intended devices and the subject is provided appropriate feedback. As a part of feedback, a graphical user interface (GUI) plays a very important role as a front end display for the BCI user and enhancing overall communication bandwidth. This paper focuses on the interface design aspect of a BCI so as to provide effective control of a wheelchair or robot arm application. A motor imagery prediction based paradigm is used to create a semi synchronous interface with a focus on presentation of a new task for selection as well as to optimally utilize the subject intentions. From a theoretical assessment, it is expected that the overall time required to select from six choices using the proposed GUI will be much less compared to existing designs. Also, being a 2 class paradigm, it is expected that the probability of error occurrence is minimized along with a quicker traverse between choices and this may allow a limited bandwidth BCI to operate an external device with multiple degree of freedom and choose from multiple different choices efficiently and effectively.
|Title of host publication||Unknown Host Publication|
|Publisher||Institution of Engineering and Technology|
|Number of pages||6|
|Publication status||Published - 2009|
|Event||2009 Irish Signals and Systems Conference - Dublin|
Duration: 1 Jan 2009 → …
|Conference||2009 Irish Signals and Systems Conference|
|Period||1/01/09 → …|
Gandhi, V., Prasad, G., Coyle, D., Behera, L., & McGinnity, TM. (2009). A Novel Paradigm for Multiple Target Selection Using a two class Brain Computer Interface. In Unknown Host Publication Institution of Engineering and Technology.