A data-driven validation of frontal EEG asymmetry using a consumer device

Friedman, David D.; Shapira, Shai; Jacobson, Liron; Gruberger, Michal

doi:10.1109/acii.2015.7344686

Cited by 8 publications

(3 citation statements)

References 40 publications

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“…For example, the widely used wireless EPOC headset (e.g., Kuan et al, 2014 ; Lin et al, 2014 ; Friedman et al, 2015 ; Yang et al, 2015 ; Gauba et al, 2017 ; Yadava et al, 2017 ; Kumar et al, 2019 ), due to its light weight, low price, and ease of use, shows promise. Studies on the EPOC headset seem to agree that it can be applied to acquire reliable EEG signals in marketing, but researchers should pay attention to its relatively low signal-to-noise ratio and poor signal stability ( Friedman et al, 2015 ). We suggest that researchers evaluate the performance of consumer-level devices using the standard testing procedures proposed by Hu et al (2019) .…”

Section: Discussionmentioning

confidence: 99%

“…Many studies have used machine learning algorithms to assess the impact of advertising. Friedman et al (2015) proposed an EEG data-driven approach to measure customers’ emotional valence when processing commercials. Their results indicated that hemispheric asymmetry was a good marker and the LMT algorithm (81.2%) provided better classification rates than the SVM algorithm (77.3%).…”

Section: Classification and Recognition Of Affective Statesmentioning

confidence: 99%

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A Literature Review of EEG-Based Affective Computing in Marketing

Pei

2021

Front. Psychol.

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Affect plays an important role in the consumer decision-making process and there is growing interest in the development of new technologies and computational approaches that can interpret and recognize the affects of consumers, with benefits for marketing described in relation to both academia and industry. From an interdisciplinary perspective, this paper aims to review past studies focused on electroencephalography (EEG)-based affective computing (AC) in marketing, which provides a promising avenue for studying the mechanisms underlying affective states and developing recognition computational models to predict the psychological responses of customers. This review offers an introduction to EEG technology and an overview of EEG-based AC; provides a snapshot of the current state of the literature. It briefly presents the themes, challenges, and trends in studies of affect evaluation, recognition, and classification; and further proposes potential guidelines for researchers and marketers.

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Section: Discussionmentioning

confidence: 99%

Section: Classification and Recognition Of Affective Statesmentioning

confidence: 99%

A Literature Review of EEG-Based Affective Computing in Marketing

Pei

2021

Front. Psychol.

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“…The Emotiv system is a low-density electrode EEG device that collects a veracious signal of underlying cortical activity, and has been used in prior studies published in leading business journals (Minas, Potter, Dennis, Bartelt, & Bae, 2014). Many studies have scrutinized the Emotiv device in a variety of settings such as examining working memory (Wang, Gwizdka, & Chaovalitwongse, 2016), auditory event-related potentials (ERPs) (Badcock et al, 2013), mobile brain-computer interfaces (Debener, Minow, Emkes, Gandras, & Vos, 2012), reliable detection of the P-300 wave and other ERPs (Ramírez-Cortes, Alarcon-Aquino, Rosas-Cholula, Gomez-Gil, & Escamilla-Ambrosio, 2010;Wang et al, 2016), human-computer interaction research (Taylor & Schmidt, 2012), hemispheric asymmetry (Friedman, Shapira, Jacobson, & Gruberger, 2015), among others. These studies have found Emotiv obtains a reliable and valid signal of underlying cortical activity and has been shown to be as good as larger high-density systems.…”

Section: Dependent Variablesmentioning

confidence: 99%

Triggering Insight: Using Neuroscience to Understand How Priming Changes Individual Cognition during Electronic Brainstorming

et al. 2017

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We build on prior theory and research on electronic brainstorming to examine how achievement priming influences individual cognition leading to changes in individual behavior and ultimately team performance. We conducted a repeated measures experiment using electroencephalography with 53 subjects performing two brainstorming tasks. We found that priming altered cognition in the left and right regions of the frontal cortex; that is, achievement priming triggered cognition in areas of the brain related to creative and insightful cognition while the placebo treatment led to cognition in areas related to language production. Thus, priming did not induce “more” cognition, but rather triggered changes in the nature of cognition that led to significantly more ideas and more ideas that were highly novel, workable, and relevant. This study makes two contributions: it shows one theoretical pathway by which achievement priming works; and it show that priming using pictures improves idea generation.

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