Shopping Dress Products in Django

The electroencephalogram (EEG) is a widely used tool for the non-invasive monitoring of the brain. However, it is very susceptible to motion artifacts, and current EEG studies are restricted to experiments where participants are stationary or perform only constrained movements, such as treadmill walking. This paper proposes a new multi-modal sensing approach for analyzing EEG collected during naturalistic free movement tasks. Co-recorded wearable eye-fixation and gyroscope data are used to identify times of interest for analysis and times of motion, and the EEG is then only analyzed during the short time periods when the eyes are fixated on wanted stimuli and there is a natural pause in the motion of the subject. We demonstrate the technique in a real-world task where subjects move round a clothes shop. This shows that in all cases, more than 65% of the time localized EEG could be analyzed, despite the free movement nature of the task. Furthermore, it can be used to demonstrate the effects of color priming in clothes shopping. We show an increase in left frontal EEG activity when participants view products matching the color background of the shop environment.