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Audience preference prediction for commercials using fNIRS
Abstract   Open access

Audience preference prediction for commercials using fNIRS

Atahan Agrali, Siddharth Bhatt, Rajneesh Suri, Kurtulus Izzetoglu, Banu Onaral and Hasan Ayaz
Frontiers in human neuroscience, v 12
2018
url
https://doi.org/10.3389/conf.fnhum.2018.227.00073View
Published, Version of Record (VoR) Open CC BY V4.0

Abstract

Advertisers rely on self-reported measures for assessing and improving the advertisements. Methods such as surveys, focus groups, interviews are extensively used specifically for commercials targeting high profile events like the Super Bowl. Consistent with the Neuroergonomics approach, brain activities measured in response to viewing of natural stimuli could be used to assess audience preferences as a more direct measure (Ariely & Berns, 2010; Dmochowski et al., 2014; Plassmann, Venkatraman, Huettel, & Yoon, 2015; Venkatraman et al., 2014). Neuroimaging tools, such as functional magnetic resonance imaging (fMRI) and Electroencephalogram (EEG), have been utilized in initial neuromarketing studies, however various limiting factors such as high operational cost, restrictions on the participant during data collection, and the speed and ease of sensor setup limit further use of these in large scale deployment as well as in actual field conditions. Functional near infrared spectroscopy (fNIRS) is the youngest and still an emerging neuroimaging technique that utilizes near infrared light to measure oxygenation changes in outer cortex. Latest generation of optical brain imaging utilizes wearable and wireless sensor pads to enable measurement of brain activity in non-tethered and ambulatory settings (Ayaz et al., 2013).

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