The designed BCI system enables real-time EEG processing in MATLAB and can be adopted for web-based remote monitoring in mobile health applications.
May support MATLAB-based real-time EEG for mHealth monitoring; leaves open clinical validation before practice adoption.
Commercially available EEG acquisition units provide ability to acquire and view EEG signals in real time using their proprietary user interface software. Analysis of such EEG data is limited to the capabilities provided within these acquisition units, thereby making it necessary to process data in multi-paradigm computing environment. Offline uploading of the data into standard tools for further analysis may cause loss of information. This paper gives details of a simple and robust mechanism for online acquisition and real time processing of EEG signals in MATLAB without any loss of information, using custom developed API. Resulting wave decomposition into discrete samples and channels also reduce complexity in processing data. The designed system, using portable wireless Emotiv EEG neuroheadset, can easily be adopted for web-based remote monitoring of live EEG for applications in the field of mobile health. Moreover, developed BCI can be miniaturised and designed as SoC (System on Chip).
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Singh et al. (2014) studied this question.
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