Dear EEGLAB list<div><br></div><div>We are very happy to announce the release of the SmartphoneBrainScanner2 platform:</div><div><br></div><div><a href="http://code.google.com/p/smartphonebrainscanner2/" target="_blank">http://code.google.com/p/smartphonebrainscanner2/</a></div>
<div><br></div><div><br></div><div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif">SmartphoneBrainScanner2</span><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"> 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.</span></div>
<div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"><br></span></div><div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"><b>Cross Platform</b></span></div>
<div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif">SmartphoneBrainScanner2</span><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"> is written in Qt</span><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif">, 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</span><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif">. Although not yet attempted, it should also work on iOS and BlackBerry</span><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"> OS.</span></div>
<div><div><br></div><div><b>Advanced EEG</b></div><div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif">SmartphoneBrainScanner2</span><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"> 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</span></div>
<div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"><br></span></div><div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif">Besides, source reconstruction methods, additional machine learning methods such as independent component analysis (ICA), common spatial patterns (CSP), and Bayesian classifiers are continuously added.</span></div>
<div><br></div><div><b>New Approach</b></div><div><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif">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</span><span style="line-height:16px;font-size:13px;font-family:arial,sans-serif"> apps can be developed just like any other apps, featuring reach interface, connectivity, etc. Go, create!</span></div>
<div><br></div><div><br></div><div><font face="arial, sans-serif"><span style="line-height:16px"><b>Developer team</b></span></font></div><div><ul><li><font face="arial, sans-serif"><span style="line-height:16px">Arkadiusz Stopczynski, DTU Informatics</span></font></li>
<li><font face="arial, sans-serif"><span style="line-height:16px">Carsten Stahlhut, DTU Informatics</span></font></li><li><font face="arial, sans-serif"><span style="line-height:16px">Michael Kai Petersen, DTU Informatics</span></font></li>
<li><font face="arial, sans-serif"><span style="line-height:16px">Jakob Eg Larsen, DTU Informatics</span></font></li><li><font face="arial, sans-serif"><span style="line-height:16px">Lars Kai Hansen, DTU Informatics</span></font></li>
</ul><div style="line-height:16px;font-family:arial,sans-serif"><br></div><div style="line-height:16px;font-family:arial,sans-serif"><br></div><span style="line-height:16px;font-family:arial,sans-serif">-- </span><br style="line-height:16px;font-family:arial,sans-serif">
<span style="line-height:16px;font-family:arial,sans-serif">Carsten Stahlhut</span><br style="line-height:16px;font-family:arial,sans-serif"><span style="line-height:16px;font-family:arial,sans-serif">Section for Cognitive Systems</span><br style="line-height:16px;font-family:arial,sans-serif">
<span style="line-height:16px;font-family:arial,sans-serif">Department of Informatics and Mathematical Modelling</span><br style="line-height:16px;font-family:arial,sans-serif"><br style="line-height:16px;font-family:arial,sans-serif">
<span style="line-height:16px;font-family:arial,sans-serif">Richard Petersens Plads, Building 321</span><br style="line-height:16px;font-family:arial,sans-serif"><span style="line-height:16px;font-family:arial,sans-serif">Technical University of Denmark</span><br style="line-height:16px;font-family:arial,sans-serif">
<span style="line-height:16px;font-family:arial,sans-serif">DK-2800 Kongens Lyngby, Denmark</span><br style="line-height:16px;font-family:arial,sans-serif"></div></div>