Multimodal Assessment of Human Innovation Perception Based on Eye Tracking, Electroencephalography and Electrocardiography

Abstract

In this work we investigate the capacity of evaluating human innovation perception from psycophysiological data, including electroencephalography (EEG), electrocardiography (ECG), and eye-gaze, measured with a wearable eye tracking device and an EEG headset. In order to do so, a dataset was collected while 36 participants watched video clips of the exterior and interior of four different car models, one of which was a futuristic concept car, under two different scenarios. The first involved a “first impressions”, unguided period and the second a guided period where participants were explicitly asked to attend to innovative areas of interest (AOI) in the vehicles. In both cases, participants reported their perceived level of innovation of the different AOIs. Experimental results showed that three metrics used for cognitive state assessment stood out for innovation perception assessment on a per-car basis, namely gaze average fixation duration, measured from the eye tracker, arousal (measured from ECG), and motivation (EEG). When averaging over cars and focusing on AOIs, in turn, cognitive load (EEG) showed importance. Lastly, while the guided protocol showed higher correlation when analyzing responses per-vehicle, the opposite behavior was observed when focusing only on AOIs, irrespective of the vehicle. In this scenario, the unguided condition resulted in higher correlation for the majority of the tested metrics.