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|Title:||Phase-based SSVEPs for real-time control of a motorised bed|
Camilleri, Tracey A.
Camilleri, Kenneth P.
Electroencephalography -- Data processing
|Publisher:||Institute of Electrical and Electronics Engineers Inc.|
|Citation:||Gauci, N., Falzon, O., Camilleri, T., & Camilleri, K. P. (2017). Phase-based SSVEPs for real-time control of a motorised bed. 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017, Jeju Island. 2080-2084.|
|Abstract:||Brain-computer interface (BCI) systems have emerged as an augmentative technology that can provide a promising solution for individuals with motor dysfunctions and for the elderly who are experiencing muscle weakness. Steadystate visually evoked potentials (SSVEPs) are widely adopted in BCI systems due to their high speed and accuracy when compared to other BCI paradigms. In this paper, we apply combined magnitude and phase features for class discrimination in a real-time SSVEP-based BCI platform. In the proposed realtime system users gain control of a motorised bed system with seven motion commands and an idle state. Experimental results amongst eight participants demonstrate that the proposed realtime BCI system can successfully discriminate between different SSVEP signals achieving high information transfer rates (ITR) of 82.73 bits/min. The attractive features of the proposed system include noninvasive recording, simple electrode configuration, excellent BCI response and minimal training requirements.|
|Appears in Collections:||Scholarly Works - CenBC|
Scholarly Works - FacEngSCE
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