[Eeglablist] Release of the SmartphoneBrainScanner2

[Carsten Stahlhut]

Dear EEGLAB list

We are very happy to announce the release of the SmartphoneBrainScanner2
platform:

http://code.google.com/p/smartphonebrainscanner2/


SmartphoneBrainScanner2 is a framework for building cross-platform
real-time EEG applications. Originally developed at the Technical
University of Denmark for collecting and analyzing signals from Emotiv EPOC
headset, its extensible architecture allows working with various EEG
systems and multiple platforms.

*Cross Platform*
SmartphoneBrainScanner2 is written in Qt, a C++ framework offering the
power of the native development and unified support for multiple platforms.
Plus the UI can be created in QML, high-level declarative UI framework.
SBS2 can be compiled for every platform supporting Qt 4, including Linux,
OSX, Windows, Android, Maemo 5, MeeGo. Although not yet attempted, it
should also work on iOS and BlackBerry OS.

*Advanced EEG*
SmartphoneBrainScanner2 contains state-of-the-art techniques for working
with multi-channel EEG signal in real-time, most notably source
reconstruction methods with online adaptation to the noise level. Current
implemented source reconstruction approaches cover the minimum-norm and low
resolution tomography (LORETA) methods formulated in a Bayesian framework
using a expectation-maximization scheme for hyperparameter estimation. The
SBS2 source reconstruction is realized using a pre-build forward model
connecting the cortical surface with the electrodes at the scalp. The
current forward model provided with the software is a 3-spheres model
obtained from the Matlab toolbox SPM8 using coarse spatial resolution and
with sensor positions in accordance with the Emotiv EPOC system

Besides, source reconstruction methods, additional machine learning methods
such as independent component analysis (ICA), common spatial patterns
(CSP), and Bayesian classifiers are continuously added.

*New Approach*
Real-time EEG doesn't have to happen in the lab! Consumer-grade and
inexpensive research neuroheadsets allow for portability, delivering
high-quality EEG signal. SmartphoneBrainScanner2 apps can be developed just
like any other apps, featuring reach interface, connectivity, etc. Go,
create!


*Developer team*

   - Arkadiusz Stopczynski, DTU Informatics
   - Carsten Stahlhut, DTU Informatics
   - Michael Kai Petersen, DTU Informatics
   - Jakob Eg Larsen, DTU Informatics
   - Lars Kai Hansen, DTU Informatics



-- 
Carsten Stahlhut
Section for Cognitive Systems
Department of Informatics and Mathematical Modelling

Richard Petersens Plads, Building 321
Technical University of Denmark
DK-2800 Kongens Lyngby, Denmark
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