ABSTRACT
A rich museum experience is one that is engaging, educating and enjoyable to the visitors, such experiences can only be achieved by personalizing and enriching the museum experience according to the visitor's state. Neural signals from the brain can provide information about the affective and cognitive state of the person implicitly. With the rise of commercial Brain-Computer Interface devices, this technology can be utilized in extracting information to adapt various experiences to the state of the person. We propose a concept and preliminary study which uses brain signals from commercial grade Brain-Computer Interface (BCI) devices to implicitly detect museum visitors' engagement in the exhibited objects. Our concept and output of the study envision an experience where real time feedback based on visitors engagement is provided and the whole museum experience is tailored to each visitor's taste. In future work, we aim to gain external validity by testing our prototype in a museum setting.
- John JB Allen and John P Kline. 2004. Frontal EEG asymmetry, emotion, and psychopathology: the first, and the next 25 years. Biological psychology 67, 1 (2004), 1--5.Google Scholar
- Marvin Andujar and Juan E Gilbert. 2013. Let's learn!: enhancing user's engagement levels through passive brain-computer interfaces. In CHI'13 Extended Abstracts on Human Factors in Computing Systems. ACM, 703--708. Google ScholarDigital Library
- Jonathan P Bowen and Silvia Filippini-Fantoni. 2004. Personalization and the web from a museum perspective. In Museums and the Web, Vol. 4.Google Scholar
- Carmen De Rojas and Carmen Camarero. 2008. Visitors' experience, mood and satisfaction in a heritage context: Evidence from an interpretation center. Tourism Management 29, 3 (2008), 525--537.Google ScholarCross Ref
- Benjamin Goldberg, Keith W Brawner, and Heather K Holden. 2012. Efficacy of Measuring Engagement during Computer-Based Training with Low-Cost Electroencephalogram (EEG) Sensor Outputs. In Proc. HFES'12. 198--202.Google ScholarCross Ref
- Dimitris Grammenos, Damien Michel, Xenophon Zabulis, and Antonis A Argyros. 2011. PaperView: augmenting physical surfaces with location-aware digital information. In Proc. TEI'11. ACM, 57--60. Google ScholarDigital Library
- D Grammenos, X Zabulis, D Michel, P Padeleris, T Sarmis, G Georgalis, P Koutlemanis, K Tzevanidis, AA Argyros, M Sifakis, and others. 2013. A prototypical interactive exhibition for the archaeological museum of thessaloniki. IJHDE 2 (2013), 75--100.Google Scholar
- Eva Hornecker. 2008. "I don't understand it either, but it is cool"-visitor interactions with a multi-touch table in a museum. In TABLETOP'08. IEEE, 113--120.Google Scholar
- Sherry Hsi and Holly Fait. 2005. RFID enhances visitors' museum experience at the Exploratorium. Commun. ACM 48, 9 (2005), 60--65. Google ScholarDigital Library
- Jin Huang, Chun Yu, Yuntao Wang, Yuhang Zhao, Siqi Liu, Chou Mo, Jie Liu, Lie Zhang, and Yuanchun Shi. 2014. FOCUS: enhancing children's engagement in reading by using contextual BCI training sessions. In Proc. CHI'14. ACM, 1905--1908. Google ScholarDigital Library
- Carrie A Joyce, Irina F Gorodnitsky, and Marta Kutas. 2004. Automatic removal of eye movement and blink artifacts from EEG data using blind component separation. Psychophysiology 41, 2 (2004), 313--325.Google ScholarCross Ref
- Rasoul Karimi, Alexandros Nanopoulos, and Lars Schmidt-Thieme. 2012. RFID-enhanced museum for interactive experience. In MM4CH. Springer, 192--205.Google Scholar
- B Joseph Pine and James H Gilmore. 1998. Welcome to the experience economy. HBR 76 (1998), 97--105.Google Scholar
- Alan T Pope, Edward H Bogart, and Debbie S Bartolome. 1995. Biocybernetic system evaluates indices of operator engagement in automated task. Biological psychology 40, 1 (1995), 187--195.Google Scholar
- Ivo Roes, Natalia Stash, Yiwen Wang, and Lora Aroyo. 2009. A personalized walk through the museum: The CHIP interactive tour guide. In CHI'09 EA. ACM, 3317--3322. Google ScholarDigital Library
- James A Russell. 1980. A circumplex model of affect. Journal of personality and social psychology 39, 6 (1980), 1161.Google ScholarCross Ref
- Stefan Schneegass, Johannes Knittel, Benjamin Rau, and Yomna Abdelrahman. 2014. Exploring Exhibits: Interactive Methods for Enriching Cultural Heritage Items. In TEI'14 EA. ACM.Google Scholar
- Alireza Sahami Shirazi, Markus Funk, Florian Pfleiderer, Hendrik Glück, and Albrecht Schmidt. 2012. MediaBrain: Annotating Videos based on Brain-Computer Interaction.. In Mensch & Computer. 263--272.Google Scholar
- Daniel Szafir and Bilge Mutlu. 2012. Pay attention!: designing adaptive agents that monitor and improve user engagement. In Proc. CHI'12. ACM, 11--20. Google ScholarDigital Library
- Jonathan R Wolpaw, Niels Birbaumer, Dennis J McFarland, Gert Pfurtscheller, and Theresa M Vaughan. 2002. Brain--computer interfaces for communication and control. Clin. neurophysio. 113, 6 (2002), 767--791.Google Scholar
- Kridsakon Yaomanee, Setha Pan-ngum, and Pasin Israsena Na Ayuthaya. 2012. Brain signal detection methodology for attention training using minimal EEG channels. In ICT'12. IEEE, 84--89.Google ScholarCross Ref
- Myeung-Sook Yoh, Joonho Kwon, and Sunghoon Kim. 2010. NeuroWander: a BCI game in the form of interactive fairy tale. In Adjunct Proc. Ubicomp'10. ACM, 389--390. Google ScholarDigital Library
- Qing Zhang and Minho Lee. 2009. Analysis of positive and negative emotions in natural scene using brain activity and GIST. Neurocomputing 72, 4 (2009), 1302--1306. Google ScholarDigital Library
Index Terms
- Implicit Engagement Detection for Interactive Museums Using Brain-Computer Interfaces
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