Endre søk
Begrens søket
1 - 17 of 17
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Treff pr side
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
Merk
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1. Astor, Philipp
    et al.
    Adam, Marc
    Jerčić, Petar
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Schaaff, Kristina
    Weinhardt, Christof
    Integrating biosignals into information systems: A NeuroIS tool for improving emotion regulation2013Inngår i: Journal of Management Information Systems, ISSN 0742-1222, E-ISSN 1557-928X, Vol. 30, nr 3, s. 247-277Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Traders and investors are aware that emotional processes can have material consequences on their financial decision performance. However, typical learning approaches for debiasing fail to overcome emotionally driven financial dispositions, mostly because of subjects' limited capacity for self-monitoring. Our research aims at improving decision makers' performance by (1) boosting their awareness to their emotional state and (2) improving their skills for effective emotion regulation. To that end, we designed and implemented a serious game-based NeuroIS tool that continuously displays the player's individual emotional state, via biofeedback, and adapts the difficulty of the decision environment to this emotional state. The design artifact was then evaluated in two laboratory experiments. Taken together, our study demonstrates how information systems design science research can contribute to improving financial decision making by integrating physiological data into information technology artifacts. Moreover, we provide specific design guidelines for how biofeedback can be integrated into information systems

  • 2.
    Hagelbäck, Johan
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Hilborn, Olle
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Jercic, Petar
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Johansson, Stefan
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Lindley, Craig
    Svensson, Johan
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Wen, Wei
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Psychophysiological Interaction and Empathic Cognition for Human-Robot Cooperative Work (PsyIntEC)2014Inngår i: Gearing Up and Accelerating Cross-Fertilization between Academic and Industrial Robotics Research in Europe: Technology Transfer Experiments from the ECHORD Project / [ed] Rohrbein, F.; Veiga, G.; Natale, C., Springer , 2014, s. 283-299Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    The aim of the PsyIntEC project is to explore affective and cognitive modeling of humans in human-robot interaction (HRI) as a basis for behavioral adaptation. To achieve this we have explored human affective perception of relevant modalities in human-human and human-robot interaction on a collaborative problem-solving task using psychophysiological measurements. The experiments conducted have given us valuable insight into the communicational and affective queues interplaying in such interactions from the human perspective. The results indicate that there is an increase in both positive and negative emotions when interacting with robots compared to interacting with another human or solving the task alone, but detailed analysis on shorter time segments is required for the results from all sensors to be conclusive and significant.

  • 3.
    Horvat, Marko
    et al.
    University of Zagreb, SRB.
    Dobrinic, Marko
    University of Zagreb, SRB.
    Novosel, Matej
    University of Zagreb, SRB.
    Jerčić, Petar
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Assessing emotional responses induced in virtual reality using a consumer EEG headset: A preliminary report2018Inngår i: 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2018, s. 1006-1010Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We report on a pilot study involving emotion elicitation in virtual reality (VR) and assessment of emotional responses with a consumer-grade EEG device. The stimulation used HTC Vive VR system showing pictures from NAPS database within a specifically designed virtual environment. The stimulation consisted of two distinct sequences with 10 pictures of happiness and 10 pictures of fear. Each picture was contained in a separate virtual room that the participants traveled through along a preset path. The estimation employed EMOTIV EPOC+ 14-channel EEG headset and a custom-developed application. The software wirelessly received EEG signals from alpha, beta low, beta high, gamma and theta bands, time-stamped them and dynamically stored in a relational database for subsequent analysis. Our preliminary results show that statistically significant correlations between valence and arousal ratings of pictures and EEG bands are present but highly personalized. Simultaneous correct placement of VR and EEG headsets is demanding and precise localization of electrodes is difficult. In fact, if emotion estimation is not strictly necessary we recommend using devices with fewer electrodes. Nevertheless, we found the EEG to be effective. By acknowledging its limitations, and using the headset in the correct context, experiments involving emotions may be significantly amended. © 2018 Croatian Society MIPRO.

  • 4.
    Jerčić, Petar
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Arousal Measurement Reflected in the Pupil Diameter for a Decision-Making Performance in Serious Games2019Inngår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer , 2019, Vol. 11863, s. 287-298Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper sets out to investigate the potentials of using pupil diameter measure as a contactless biofeedback method. The investigation was performed on how the interdependent and competing activation of the autonomic nervous system is reflected in the pupil diameter and how it affects the performance on decision-making task in serious games. The on-line biofeedback based on physiological measurements of arousal was integrated into the serious game set in the financial context. The pupil diameter was validated against the heart rate data measuring arousal, where the effects of such arousal were investigated. It was found that the physiological arousal was observable on both the heart and pupil data. Furthermore, the participants with lower arousal took less time to reach their decisions, and those decisions were more successful, in comparison to the participants with higher arousal. Moreover, such participants were able to get a higher total score and finish the game. This study validated the potential usage of pupil diameter as an unobtrusive measure of biofeedback, which would be beneficial for the investigation of arousal on human decision-making inside of serious games. © IFIP International Federation for Information Processing, 2019.

  • 5.
    Jerčić, Petar
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Design and Evaluation of Affective Serious Games for Emotion Regulation Training2013Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Emotions are thought to be a key factor that critically influences human decision-making. Emotion regulation can help to mitigate emotion related decision biases and eventually lead to a better decision performance. Serious games emerged as a new angle introducing technological methods to learning emotion regulation, where meaningful biofeedback information displays player's emotional state. This thesis investigates emotions and the effect of emotion regulation on decision performance. Furthermore, it explores design and evaluation methods for creating serious games where emotion regulation can be learned and practiced. The scope of this thesis was limited to serious games for emotion regulation training using psychophysiological methods to communicate user's affective information. Using the psychophysiological methods, emotions and their underlying neural mechanism have been explored. Through design and evaluation of serious games using those methods, effects of emotion regulation have been investigated where decision performance has been measured and analyzed. The proposed metrics for designing and evaluating such affective serious games have been exhaustively evaluated. The research methods used in this thesis were based on both quantitative and qualitative aspects, with true experiment and evaluation research, respectively. Serious games approach to emotion regulation was investigated. The results suggested that two different emotion regulation strategies, suppression and cognitive reappraisal, are optimal for different decision tasks contexts. With careful design methods, valid serious games for training those different strategies could be produced. Moreover, using psychophysiological methods, underlying emotion neural mechanism could be mapped to provide optimal level of arousal for a certain task. The results suggest that it is possible to design and develop serious game applications that provide helpful learning environment where decision makers could practice emotion regulation and subsequently improve their decision making.

  • 6.
    Jerčić, Petar
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    The Effects of Emotions and Their Regulation on Decision-making Performance in Affective Serious Games2019Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Emotions are thought to be one of the key factors that critically influence human decision-making. Emotion-regulation can help to mitigate emotion-related decision biases and eventually lead to a better decision performance. Serious games emerged as a new angle introducing technological methods to practicing emotion-regulation, where meaningful biofeedback information communicates player's affective states to a series of informed gameplay choices. These findings motivate the notion that in the decision context of serious games, one would benefit from awareness and regulation of such emerging emotions.

    This thesis explores the design and evaluation methods for creating serious games where emotion-regulation can be practiced using physiological biofeedback measures. Furthermore, it investigates emotions and the effect of emotion-regulation on decision performance in serious games. Using the psychophysiological methods in the design of such games, emotions and their underlying neural mechanism have been explored.

    The results showed the benefits of practicing emotion-regulation in serious games, where decision-making performance was increased for the individuals who down-regulated high levels of arousal while having an experience of positive valence. Moreover, it increased also for the individuals who received the necessary biofeedback information. The results also suggested that emotion-regulation strategies (i.e., cognitive reappraisal) are highly dependent on the serious game context. Therefore, the reappraisal strategy was shown to benefit the decision-making tasks investigated in this thesis. The results further suggested that using psychophysiological methods in emotionally arousing serious games, the interplay between sympathetic and parasympathetic pathways could be mapped through the underlying emotions which activate those two pathways. Following this conjecture, the results identified the optimal arousal level for increased performance of an individual on a decision-making task, by carefully balancing the activation of those two pathways. The investigations also validated these findings in the collaborative serious game context, where the robot collaborators were found to elicit diverse affect in their human partners, influencing performance on a decision-making task. Furthermore, the evidence suggested that arousal is equally or more important than valence for the decision-making performance, but once optimal arousal has been reached, a further increase in performance may be achieved by regulating valence. Furthermore, the results showed that serious games designed in this thesis elicited high physiological arousal and positive valence. This makes them suitable as research platforms for the investigation of how these emotions influence the activation of sympathetic and parasympathetic pathways and influence performance on a decision-making task.

    Taking these findings into consideration, the serious games designed in this thesis allowed for the training of cognitive reappraisal emotion-regulation strategy on the decision-making tasks. This thesis suggests that using evaluated design and development methods, it is possible to design and develop serious games that provide a helpful environment where individuals could practice emotion-regulation through raising awareness of emotions, and subsequently improve their decision-making performance.

  • 7.
    Jerčić, Petar
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    What could the baseline measurements predict about decision-making performance in serious games set in the financial context2019Inngår i: 2019 11th International Conference on Virtual Worlds and Games for Serious Applications, VS-Games 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2019Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper sets out to investigate how the basal activation of the parasympathetic and sympathetic nervous systems may affect and predict the decision-making performance of players in serious games. In order to investigate the basal activation of both branches of the autonomic nervous system, pupil diameter and heart rate were recorded during baseline and analyzed in regards to performance scores in the serious game. It was found that the balance between the parasympathetic and sympathetic activation was responsible for beneficial decision-making performance, while lower sympathetic activation was found to be associated with the higher level reached in the game. It is suggested that the balance between the basal activation of both branches of the autonomic nervous system recorded during the baseline may predict the decision-making performance of players on the subsequent tasks in serious games. © 2019 IEEE.

  • 8.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Astor, Philipp J
    FZI Forschungszentrum Informatik, DEU.
    Adam, Marc
    Karlsruhe Institute of Technology, DEU.
    Hilborn, Olle
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Schaff, Kristina
    FZI Forschungszentrum Informatik, DEU.
    Lindley, Craig
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Sennersten, Charlotte
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Eriksson, Jeanette
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    A Serious Game using Physiological Interfaces for Emotion Regulation Training in the context of Financial Decision-Making2012Inngår i: ECIS 2012 - Proceedings of the 20th European Conference on Information Systems, AIS Electronic Library (AISeL) , 2012, s. 1-14Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Research on financial decision-making shows that traders and investors with high emotion regulation capabilities perform better in trading. But how can the others learn to regulate their emotions? ‘Learning by doing’ sounds like a straightforward approach. But how can one perform ‘learning by doing’ when there is no feedback? This problem particularly applies to learning emotion regulation, because learners can get practically no feedback on their level of emotion regulation. Our research aims at providing a learning environment that can help decision-makers to improve their emotion regulation. The approach is based on a serious game with real-time biofeedback. The game is settled in a financial context and the decision scenario is directly linked to the individual biofeedback of the learner’s heart rate data. More specifically, depending on the learner’s ability to regulate emotions, the decision scenario of the game continuously adjusts and thereby becomes more (or less) difficult. The learner wears an electrocardiogram sensor that transfers the data via Bluetooth to the game. The game itself is evaluated at several levels.

  • 9.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Cederholm, Henrik
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    The Future of Brain-Computer Interface for Games and Interaction Design2010Rapport (Annet vitenskapelig)
  • 10.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Hagelbäck, Johan
    Linnéuniversitetet, SWE.
    Lindley, Craig
    Computational Modelling Group, Data61, CSIRO, AUS.
    An affective serious game for collaboration between humans and robots2019Inngår i: Entertainment Computing, ISSN 1875-9521, E-ISSN 1875-953X, Vol. 32, artikkel-id 100319Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Elicited physiological affect in humans collaborating with their robot partners was investigated to determine its influence on decision-making performance in serious games. A turn-taking version of the Tower of Hanoi game was used, where physiological arousal and valence underlying such human-robot proximate collaboration were investigated. A comparable decision performance in the serious game was found between human and non-humanoid robot arm collaborator conditions, while higher physiological affect was found in humans collaborating with such robot collaborators. It is suggested that serious games which are carefully designed to take into consideration the elicited physiological arousal might witness a better decision-making performance and more positive valence using non-humanoid robot partners instead of human ones. © 2019 The Authors

  • 11.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Hagelbäck, Johan
    Linnaeus University, SWE.
    Lindley, Craig
    CSIRO ICT Centre, AUS.
    Physiological Affect and Performance in a Collaborative Serious Game Between Humans and an Autonomous Robot2018Inngår i: Lect. Notes Comput. Sci., Springer Verlag , 2018, Vol. 11112, s. 127-138Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper sets out to examine how elicited physiological affect influences the performance of human participants collaborating with the robot partners on a shared serious game task; furthermore, to investigate physiological affect underlying such human-robot proximate collaboration. The participants collaboratively played a turn-taking version of a serious game Tower of Hanoi, where physiological affect was investigated in a valence-arousal space. The arousal was inferred from the galvanic skin response data, while the valence was inferred from the electrocardiography data. It was found that the robot collaborators elicited a higher physiological affect in regard to both arousal and valence, in contrast to their human collaborator counterparts. Furthermore, a comparable performance between all collaborators was found on the serious game task. © 2018, IFIP International Federation for Information Processing.

  • 12.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Sennersten, Charlotte
    CSIRO Mineral Resources, AUS.
    Lindley, Craig
    Intelligent Sensing and Systems Laboratory, CSIRO ICT Centre, AUS .
    Modeling cognitive load and physiological arousal through pupil diameter and heart rate2018Inngår i: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This study investigates individuals’ cognitive load processing abilities while engaged on a decision-making task in serious games, to explore how a substantial cognitive load dominates over the physiological arousal effect on pupil diameter. A serious game was presented to the participants, which displayed the on–line biofeedback based on physiological measurements of arousal. In such dynamic decision-making environment, the pupil diameter was analyzed in relation to the heart rate, to evaluate if the former could be a useful measure of cognitive abilities of individuals. As pupil might reflect both cognitive activity and physiological arousal, the pupillary response will show an arousal effect only when the cognitive demands of the situation are minimal. Evidence shows that in a situation where a substantial level of cognitive activity is required, only that activity will be observable on the pupil diameter, dominating over the physiological arousal effect indicated by the pupillary response. It is suggested that it might be possible to design serious games tailored to the cognitive abilities of an individual player, using the proposed physiological measurements to observe the moment when such dominance occurs. © 2018, The Author(s).

  • 13.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Sennersten, Charlotte
    CSIRO Mineral Resources, AUS.
    Lindley, Craig
    Intelligent Sensing and Systems Laboratory, AUS.
    The effect of cognitive load on physiological arousal in a decision-making serious game2017Inngår i: 2017 9th International Conference on Virtual Worlds and Games for Serious Applications, VS-Games 2017 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2017, s. 153-156, artikkel-id 8056587Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The aim of this paper is to investigate how a substantial cognitive load overshadows the physiological arousal effect, in an attempt to study cognitive abilities of participants engaged on decision-making tasks in serious games. Participants were engaged in a dynamic serious game environment displaying online biofeedback based on the physiological measurements of arousal. The pupil diameter was analyzed in relation to the heart rate during a challenging decision-making task. It was found that the moment when a substantial cognitive load overshadows the physiological arousal effect is observable on the pupil diameter in relation to the heart rate. © 2017 IEEE.

  • 14.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Sundstedt, Veronica
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Practicing Emotion-Regulation Through Biofeedback on the Decision-Making Performance in the Context of Serious Games: a Systematic Review2019Inngår i: Entertainment Computing, ISSN 1875-9521, E-ISSN 1875-953X, Vol. 29, s. 75-86Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Evidence shows that emotions critically influence human decision-making. Therefore, emotion-regulation using biofeedback has been extensively investigated. Nevertheless, serious games have emerged as a valuable tool for such investigations set in the decision-making context. This review sets out to investigate the scientific evidence regarding the effects of practicing emotion-regulation through biofeedback on the decision-making performance in the context of serious games. A systematic search of five electronic databases (Scopus, Web of Science, IEEE, PubMed Central, Science Direct), followed by the author and snowballing investigation, was conducted from a publication's year of inception to October 2018. The search identified 16 randomized controlled experiment/quasi-experiment studies that quantitatively assessed the performance on decision-making tasks in serious games, involving students, military, and brain-injured participants. It was found that the participants who raised awareness of emotions and increased the skill of emotion-regulation were able to successfully regulate their arousal, which resulted in better decision performance, reaction time, and attention scores on the decision-making tasks. It is suggested that serious games provide an effective platform validated through the evaluative and playtesting studies, that supports the acquisition of the emotion-regulation skill through the direct (visual) and indirect (gameplay) biofeedback presentation on decision-making tasks.

  • 15.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Wen, Wei
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för teknik och estetik. Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    Hagelbäck, Johan
    Linnéuniversitetet, SWE.
    Sundstedt, Veronica
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
    The Effect of Emotions and Social Behavior on Performance in a Collaborative Serious Game Between Humans and Autonomous Robots2018Inngår i: International Journal of Social Robotics, ISSN 1875-4791, E-ISSN 1875-4805, Vol. 10, nr 1, s. 115-129Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The aim of this paper is to investigate performance in a collaborative human–robot interaction on a shared serious game task. Furthermore, the effect of elicited emotions and perceived social behavior categories on players’ performance will be investigated. The participants collaboratively played a turn-taking version of the Tower of Hanoi serious game, together with the human and robot collaborators. The elicited emotions were analyzed in regards to the arousal and valence variables, computed from the Geneva Emotion Wheel questionnaire. Moreover, the perceived social behavior categories were obtained from analyzing and grouping replies to the Interactive Experiences and Trust and Respect questionnaires. It was found that the results did not show a statistically significant difference in participants’ performance between the human or robot collaborators. Moreover, all of the collaborators elicited similar emotions, where the human collaborator was perceived as more credible and socially present than the robot one. It is suggested that using robot collaborators might be as efficient as using human ones, in the context of serious game collaborative tasks.

  • 16. Peffer, Gilbert
    et al.
    Cederholm, Henrik
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Clough, Gill
    Jerčić, Petar
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Evaluating Games Designed to Improve Financial Capability2010Rapport (Annet vitenskapelig)
  • 17.
    Sohaib, Ahmad Tauseef
    et al.
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Qureshi, Shahnawaz
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Hagelbäck, Johan
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Hilborn, Olle
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Jerčić, Petar
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Evaluating classifiers for emotion recognition using EEG2013Konferansepaper (Fagfellevurdert)
    Abstract [en]

    There are several ways of recording psychophysiology data from humans, for example Galvanic Skin Response (GSR), Electromyography (EMG), Electrocardiogram (ECG) and Electroencephalography (EEG). In this paper we focus on emotion detection using EEG. Various machine learning techniques can be used on the recorded EEG data to classify emotional states. K-Nearest Neighbor (KNN), Bayesian Network (BN), Artificial Neural Network (ANN) and Support Vector Machine (SVM) are some machine learning techniques that previously have been used to classify EEG data in various experiments. Five different machine learning techniques were evaluated in this paper, classifying EEG data associated with specific affective/emotional states. The emotions were elicited in the subjects using pictures from the International Affective Picture System (IAPS) database. The raw EEG data were processed to remove artifacts and a number of features were selected as input to the classifiers. The results showed that it is difficult to train a classifier to be accurate over large datasets (15 subjects) but KNN and SVM with the proposed features were reasonably accurate over smaller datasets (5 subjects) identifying the emotional states with an accuracy up to 77.78%.

1 - 17 of 17
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf