The emergence of low cost electroencephalography (EEG) wireless neuroheadsets may potentially turn smartphones into pocketable labs , and enable design of personalized interfaces that adapt the selection of media to our emotional responses when viewing images and reading text. However such EEG responses are characterized by only small voltage changes that have typically been found in group studies involving multiple trials and large numbers of participants. Hypothesizing that spatial filtering might enhance retrieval, we apply independent component analysis (ICA) to cluster scalp maps and time series responses in a single subject based on only a few trials. Comparing our results against previous findings we identify multiple early and late ICA components that are similarly modulated by neutral, pleasant and unpleasant content in both images and words. Suggesting that we might be able to model emotional responses elicited from individual users browsing media content, which could in long term be integrated into cognitive interfaces that adapt to our preferences.
|Number of pages||1|
|Publication status||Published - 2014|
|Event||36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States|
Duration: 26 Aug 2014 → 30 Aug 2014
Conference number: 36
|Conference||36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Period||26/08/2014 → 30/08/2014|