@CONFERENCE\{IMM2011-06124, author = "M. K. Petersen and C. Stahlhut and A. Stopczynski and J. E. Larsen and L. K. Hansen", title = "Smartphones get emotional: mind reading images and reconstructing the neural sources", year = "2011", month = "oct", booktitle = "Affective Computing and Intelligent Interaction", volume = "", series = "", editor = "1st workshop on machine learning for affective computing", publisher = "", organization = "", address = "", url = "http://www2.compute.dtu.dk/pubdb/pubs/6124-full.html", abstract = "Combining a 14 channel neuroheadset with a smartphone to capture and process brain imaging data, we demonstrate the ability to distinguish among emotional responses reflected in different scalp potentials when viewing pleasant and unpleasant pictures compared to neutral content. Clustering independent components across subjects we are able to remove artifacts and identify common sources of synchronous brain activity, consistent with earlier findings based on conventional {EEG} equipment. Applying a Bayesian approach to reconstruct the neural sources not only facilitates differentiation of emotional responses but may also provide an intuitive interface for interacting with a {3D} rendered model of brain activity. Integrating a wireless {EEG} set with a smartphone thus offers completely new opportunities for modeling the mental state of users as well as providing a basis for novel bio-feedback applications." }