EEG-Based Measurement of Subjective Parameters in Evaluations

Cernea, Daniel; Olech, Peter-Scott; Ebert, Achim; Kerren, Andreas

doi:10.1007/978-3-642-22095-1_57

Cited by 21 publications

(16 citation statements)

References 7 publications

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“…The model of emotion used in the EPOC device was constructed from data collected from over one hundred volunteers (Inventado et al, 2011). The validity of the data has been proved by studies conducted by Cernea et al (2011), who presented a comparison between subjective emotions (questionnaires) and the measurements obtained using Emotiv EPOC headsets. The results of this study suggested that wireless EEG technology is capable of measuring subjectivity in the assessment of product and service satisfaction.…”

Section: Figure 1 Positioning Of the Electrodes Upon The Scalp (Emotmentioning

confidence: 99%

Users’ reactions captured by means of an EEG headset on viewing the presentation of sustainable designs using verbal narrative

Royo

Chulvi

Mulet

et al. 2018

EJM

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The aim of this paper is to determine whether consumers accept new arguments for choosing a product that adapts to future needs. It is also seeks to investigate whether the design of products and their ensuing advertising and promotion through a sustainable approach by means of verbal narrative ads can generate a more positive emotional response in the future users of the product than with the application of visual narrative ads.To this end, an experiment was conducted consisting in consumers, with and without experience with the product, watching a promotional video based on verbal narrative, created using the new usage scenarios approach, in which the advantages of a sustainable product are shown. The neuronal response of the possible users was then measured by means of the EEG headset. In order to be able to establish a comparison, the same response was also measured in the same consumers when they viewed a commercial video based on visual narrative about a product with similar characteristics.The results show, among other conclusions, that viewing the verbal narrative ad first triggers higher emotional values of excitement, both in the short and the long term, as well as frustration. It is also observed that having no experience with the product causes higher meditation values. 2This can be useful to enterprises both in order to design their products in such a way as to orientate them towards consumer concerns, and to design advertisements in such a way as to link consumers emotionally with the product.Keywords -advertising, usage scenarios, measured emotions, sustainable products, marketing research. This study has been possible thanks to the research projects 15I336.01/1 "El arte y el diseño en la nueva sociedad digital" funded by the Universitat Jaume I. The authors also wish to acknowledge the help of Sara Romero, María Agost, Laura Martínez and all the participants in the experiment.

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Section: Figure 1 Positioning Of the Electrodes Upon The Scalp (Emotmentioning

confidence: 99%

Users’ reactions captured by means of an EEG headset on viewing the presentation of sustainable designs using verbal narrative

Royo

Chulvi

Mulet

et al. 2018

EJM

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“…We broadly classify these efforts into two categories: BCIs based on event-related (de)synchronization (ERD or ERS) [4,21,30,32,33,35,40], and BCIs based on steady-state visual evoked potentials (SSVEPs) [16,23,26,36,38]. Then, we discuss some works that use Emotiv EPOC EEG headsets [5,6,11,29,41]. …”

Section: Related Workmentioning

confidence: 99%

“…BCIs based on steadystate visual evoked potentials (SSVEPs) have also been significantly researched [16,23,26,36,38], but SSVEP BCIs do not work for some patients [27,28]. EEG-based BCIs have been studied as well [5,6,11,29,41], but most of them are not under an online processing. Exploring EEG headsets to control cyber-physical systems is not new.…”

Section: Introductionmentioning

confidence: 99%

Towards an EEG-based brain-computer interface for online robot control

Zhou

Graham

et al. 2015

Multimed Tools Appl

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According to New York Times, 5.6 million people in the United States are paralyzed to some degree. Motivated by requirements of these paralyzed patients in controlling assisted-devices that support their mobility, we present a novel EEG-based BCI system, which is composed of an Emotive EPOC neuroheadset, a laptop and a Lego Mindstorms NXT robot in this paper. We provide online learning algorithms that consist of k-means clustering and principal component analysis to classify the signals from the headset into corresponding action commands. Moreover, we also discuss how to integrate the Emotiv EPOC headset into the system, and how to integrate the LEGO robot. Finally, we evaluate the proposed online learning algorithms of our BCI system in terms of precision, recall, and the F -measure, and our results show that the algorithms can accurately classify the subjects' thoughts into corresponding action commands.

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“…15,23,24 The importance of detecting and classifying these emotions increases as one considers that user emotional states are usually generated by stimulus events, 25 events which in our context can be related to the applications the users interact with. As a result, emotions might be closely connected to the visual systems users interact with (e.g., frustration about an unintuitive representation), to the task they have to execute (e.g., excitement after having an insight), or even to the other users they collaborate with (e.g., group tensions).…”

Section: Emotion-printsmentioning

confidence: 99%

“…Note that the BCI-based detection of user emotional states is beyond the scope of this paper, and that the Emotiv technology and its corresponding framework have been previously evaluated in the context of emotion reporting. 16,24 Also, the EPOC headset and similar BCI systems have been used successfully in various subjectivity and state-based evaluations, including some in the field of visualization. 23,34 In our study, coupling both the facial expression readings and the classification of a↵ective states generated by the EPOC framework supplied us with values for the emotions that are closest to the extremes of the arousal-valence axes in Russell's circumplex model, and which can be employed to cover the entire corresponding 2D space.…”

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confidence: 99%

Emotion-prints: interaction-driven emotion visualization on multi-touch interfaces

et al. 2015

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Emotions are one of the unique aspects of human nature, and sadly at the same time one of the elements that our technological world is failing to capture and consider due to their subtlety and inherent complexity. But with the current dawn of new technologies that enable the interpretation of emotional states based on techniques involving facial expressions, speech and intonation, electrodermal response (EDS) and brain-computer interfaces (BCIs), we are finally able to access real-time user emotions in various system interfaces. In this paper we introduce emotion-prints, an approach for visualizing user emotional valence and arousal in the context of multi-touch systems. Our goal is to o↵er a standardized technique for representing user a↵ective states in the moment when and at the location where the interaction occurs in order to increase a↵ective self-awareness, support awareness in collaborative and competitive scenarios, and o↵er a framework for aiding the evaluation of touch applications through emotion visualization. We show that emotion-prints are not only independent of the shape of the graphical objects on the touch display, but also that they can be applied regardless of the acquisition technique used for detecting and interpreting user emotions. Moreover, our representation can encode any a↵ective information that can be decomposed or reduced to Russell's two-dimensional space of valence and arousal. Our approach is enforced by a BCI-based user study and a follow-up discussion of advantages and limitations.

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EEG-Based Measurement of Subjective Parameters in Evaluations

Cited by 21 publications

References 7 publications

Users’ reactions captured by means of an EEG headset on viewing the presentation of sustainable designs using verbal narrative

Users’ reactions captured by means of an EEG headset on viewing the presentation of sustainable designs using verbal narrative

Towards an EEG-based brain-computer interface for online robot control

Emotion-prints: interaction-driven emotion visualization on multi-touch interfaces

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