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2015 | 5 | 75--80
Tytuł artykułu

Emotion Monitor - Concept, Construction and Lessons Learned

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper concerns the design and physical construction of an emotion monitor stand for tracking human emotions in Human-Computer Interaction using multi-modal approach. The concept of the stand using cameras, behavioral analysis tools and a set of physiological sensors such as galvanic skin response, blood-volume pulse, temperature, breath and electromyography is presented and followed by details of Emotion Monitor construction at Gdansk University of Technology. Some experiments are reported that were already held at the stand, providing observations on reliability, accuracy and value the stand might provide in human-systems interaction evaluation. The lessons learned at this particular stand might be interesting for the other researchers aiming at emotion monitoring in human-systems interaction. (original abstract)
Rocznik
Tom
5
Strony
75--80
Opis fizyczny
Twórcy
  • Gdansk University of Technology
Bibliografia
  • Szwoch W. (2013) Using physiological signals for emotion recognition, In Proc of HSI, Gdańsk, Poland, 556-561.
  • Zeng Z, Pantic M, Roisman G, Huang T.S (2009) A survey of affect recognition methods: Audio, visual, and spontaneous expressions. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 31(1), 39-58
  • Kołakowska A. (2013) A review of emotion recognition methods based on keystroke dynamics and mouse movements, In Proc of HSI, Gdańsk, Poland, 548-555.
  • Cambria, E, Schuller, B, Xia, YQ, Havasi, C (2013) New avenues in opinion mining and sentiment analysis. IEEE Intell Syst 28: pp. 15-21
  • Partala T., Surakka V. (2004) The effect of affective interventions in human-computer interaction, Interacting with Computers, 16, pp. 295-309
  • Hazlett R., Benedek J. (2007) Measuring emotional valence to understand the user's experience of software, Int. J. Human-Computer Studies, 65, 306-314.
  • Zimmermann P., Gomez P., Danuser B., Schar S. (2006) Extending usability: putting affect into the user-experience, In Proc. of Nordic Conf. on Human-Computer Interaction, Oslo, pp 27-32.
  • Kołakowska A, Landowska A, Szwoch M, Szwoch W, Wrobel M R (2013) Emotion Recognition and its Application in Software Engineering, In Proc of HSI, Gdańsk, Poland, 532-539.
  • Wróbel M.R. (2013) Emotions in the software development process, In Proc of HSI, Gdańsk, Poland, 518-523.
  • Binali H, Wu C, Potdar V (2009) A new significant area: Emotion detection in e-learning using opinion mining techniques. In: Proc. of 3rd IEEE International Conference on Digital Ecosystems and Technologies, 2009, 259-264
  • Landowska A (2013) Affective computing and affective learning - methods, tools and prospects, EduAction. Electronic education magazine, 1(5), 16-31
  • Landowska A. (2013) Affective computing and affective learning - methods, tools and prospects, EduAction. Electronic education magazine, 1, 5, pp. 16-31
  • Chittaro L., Sioni R. (2014) Affective Computing vs. Affective Placebo: Study of a Biofeedback-Controlled Game for Relaxation Training. International Journal of Human-Computer Studies, 72, 8-9, pp. 663-73. doi:10.1016/j.ijhcs.2014.01.007.
  • Gunes H., Schuller B. (2013) Categorical and dimensional affect analysis in continuous input: Current trends and future directions, Image and Vision Computing, 31, pp. 120-136
  • Bailenson J.N., Pontikakis E.D., Mauss I.B., Gross J.J., Jabon M.E, Hutcherson C.A.C., Nass C., John O. (2008) Real-time classification of evoked emotions using facial feature tracking and physiological responses, International journal of human-computer studies, 66(5), 303-317
  • Picard R, Daily S (2005) Evaluating affective interactions: Alternatives to asking what users feel. In CHI Workshop on Evaluating Affective Interfaces: Innovative Approaches
  • Ling H.S., Bali R, Salam R.A. (2006) Emotion detection using keywords spotting and semantic network, In Computing & Informatics, IEEE, 1-5
  • Landowska A, Szwoch W, Szwoch M, (2015) Methodology of Affective Intervention Design for Intelligent Systems, Interactions with Computers (unpublished).
  • Gunes H. and Piccardi M (2005) Affect Recognition from Face and Body: Early Fusion versus Late Fusion, Proc. IEEE International Conference on Systems, Man and Cybernetics, pp. 3437-3443.
  • Hupont I; Ballano S; Baldassarri S.; Cerezo, E, (2011) Scalable multimodal fusion for continuous affect sensing, IEEE Workshop on Affective Computational Intelligence (WACI), pp.1,8, 11-15
  • Landowska A.: Emotion monitoring - verification of physiological characteristics measurement procedures, Metrology and Measurement Systems Journal, Vol XXI, No. 4, 2014, pp. 719-732.
  • Landowska A, Karpienko K, Wróbel M, Jędrzejewska-Szczerska M (2014) Selection of physiological parameters for optoelectronic system supporting behavioral therapy of autistic children, Proc. SPIE Vol. 9290, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments.
  • Jędrzejewska-Szczerska M, Karpienko K, Landowska A (2015), System supporting behavioral therapy for children with autism, Journal of Innovative Optical Health Sciences Vol. 8, No. 3, 1541008
  • & Landowska A, Wrobel M (2015) Affective reactions to playing digital games, Int. conf. on Human-Systems Interaction, Warsaw, Poland, pp. 264-270
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171418560

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