BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038447
A. Väljamäe, L. Evers, B. Allison, J. Ongering, A. Riccio, Irene Ingardi, D. Lamas
{"title":"The BrainHack Project: Exploring Art - BCI Hackathons","authors":"A. Väljamäe, L. Evers, B. Allison, J. Ongering, A. Riccio, Irene Ingardi, D. Lamas","doi":"10.1145/3038439.3038447","DOIUrl":"https://doi.org/10.1145/3038439.3038447","url":null,"abstract":"The main goal of the BrainHack project is to engage the international artistic community experimenting with Brain Neural Computer Interaction (BNCI) technologies and link it to the BNCI scientific community. BrainHack explores hackathons format to enhance the experimentation with non-clinical and artistic uses of BNCI. Here we briefly summarize the two \"Hack the Brain\" hackathons of 2016 and highlight the importance of match-making process, ready-made prototypes that can be \"hacked\" during the hackathon, and repository of the previous works and associated information, software and data. We also discuss the strategy for the upcoming art - BCI hackathons.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122403572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038445
Oswald Barral, Ilkka Kosunen, Tuukka Ruotsalo, Michiel M. A. Spapé, M. Eugster, N. Ravaja, Samuel Kaski, Giulio Jacucci
{"title":"BCI for Physiological Text Annotation","authors":"Oswald Barral, Ilkka Kosunen, Tuukka Ruotsalo, Michiel M. A. Spapé, M. Eugster, N. Ravaja, Samuel Kaski, Giulio Jacucci","doi":"10.1145/3038439.3038445","DOIUrl":"https://doi.org/10.1145/3038439.3038445","url":null,"abstract":"Automatic annotation of media content has become a critically important task for many digital services as the quantity of available online media content has grown exponentially. One approach is to annotate the content using the physiological responses of the media consumer. In the present paper, we reflect on three case studies that use brain signals for implicit text annotation to discuss the challenges faced when bringing passive brain-computer interfaces for physiological text annotation to the real world.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121728908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038446
Y. O. Nuzhdin, S. Shishkin, A. A. Fedorova, A. Trofimov, E. P. Svirin, B. Kozyrskiy, A. A. Medyntsev, Ignat A. Dubynin, B. Velichkovsky
{"title":"The Expectation Based Eye-Brain-Computer Interface: An Attempt of Online Test","authors":"Y. O. Nuzhdin, S. Shishkin, A. A. Fedorova, A. Trofimov, E. P. Svirin, B. Kozyrskiy, A. A. Medyntsev, Ignat A. Dubynin, B. Velichkovsky","doi":"10.1145/3038439.3038446","DOIUrl":"https://doi.org/10.1145/3038439.3038446","url":null,"abstract":"In this preliminary study we tested online a new Eye-Brain-Computer Interface (EBCI) for selection of positions on a screen with a combination of gaze based control and a passive brain-computer interface (BCI). This hybrid BCI was trained offline to recognize the electroencephalogram (EEG) patterns recorded during gaze dwells intentionally used to make moves in a computer game. The patterns were presumably related to expectation of the interface feedback. In the online test, 500 ms gaze dwells led to actions each time the BCI classified them as intentional. When the BCI made a miss, a participant could still communicate the intention by prolonging the dwell up to 1000 ms. Also playing the game was possible, it was found that defining the ground truth for such an online system is not trivial and that further efforts will be needed to evaluate the performance of the expectation based EBCI reliably.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133636225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038440
A. Brouwer, J. V. D. Waa, M. Hogervorst, A. Cacace, H. Stokking
{"title":"A Feasible BCI in Real Life: Using Predicted Head Rotation to Improve HMD Imaging","authors":"A. Brouwer, J. V. D. Waa, M. Hogervorst, A. Cacace, H. Stokking","doi":"10.1145/3038439.3038440","DOIUrl":"https://doi.org/10.1145/3038439.3038440","url":null,"abstract":"While brain signals potentially provide us with valuable information about a user, it is not straightforward to derive and use this information to smooth man-machine interaction in a real life setting. We here propose to predict head rotation on the basis of brain signals in order to improve images presented in a Head Mounted Display (HMD). Previous studies based on arm and leg movements suggest that this could be possible, and a pilot study showed promising results. From the perspective of the field of Brain-Computer Interfaces (BCI), this application provides a good case to put the field's achievements to the test and to further develop in the context of a real life application. The main reason for this is that within the proposed application, acquiring accurately labeled training data (whether and which head movement took place) and monitoring of the quality of the predictive model can happen on the fly. From the perspective of HMD technology and Intelligent User Interfaces, the proposed BCI potentially improves user experience and enables new types of immersive applications.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129088051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038443
Ilkka Kosunen, Antti Ruonala, M. Salminen, Simo Järvelä, N. Ravaja, Giulio Jacucci
{"title":"Neuroadaptive Meditation in the Real World","authors":"Ilkka Kosunen, Antti Ruonala, M. Salminen, Simo Järvelä, N. Ravaja, Giulio Jacucci","doi":"10.1145/3038439.3038443","DOIUrl":"https://doi.org/10.1145/3038439.3038443","url":null,"abstract":"Meditation and mindfulness techniques are useful for both treatment of various disorders as well as improving the quality of life in general. Meditation offers intriguing possibilities for BCI as it is targeted at able-bodied general population and goes beyond the traditional explicit control BCI paradigm. In previous work, we have shown how neurofeedback can be successfully applied in a laboratory setting to improve the meditation experience. This position paper aims to expand this work in two ways. First, we explore the problems and issues that might arise when moving from the laboratory setting to the normal, everyday world. Second, we will consider the possibilities of extending the neurofeedback with other forms of physiological computing. Our position is that meditation and relaxation applications provide a perfect application area for bringing BCI into the real world.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129149567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038442
K. Pollmann, Daniel Ziegler, M. Peissner, Mathias Vukelić
{"title":"A New Experimental Paradigm for Affective Research in Neuro-adaptive Technologies","authors":"K. Pollmann, Daniel Ziegler, M. Peissner, Mathias Vukelić","doi":"10.1145/3038439.3038442","DOIUrl":"https://doi.org/10.1145/3038439.3038442","url":null,"abstract":"One core challenge in the field of neuro-adaptive technology is the detection of the current mental user state. Existing experimental paradigms use established stimulus material (e.g. pictures) to induce affective user states and make them measurable. Since these paradigms lack ecological validity, there is a pressing need to design more interactive stimulus material that allows a reliably and systematical induction of different affective user states in more realistic scenarios. We present and empirically validate a new experimental paradigm featuring a simulated adaptive system that induces positive and negative affective user states through supporting or impeding goal achievement during a navigation task. Furthermore, we tested the feasibility of quantifying underlying neurophysiological processes of affective states by simultaneous investigations of electroencephalographic and functional near-infrared spectroscopic. These investigations further show the effectiveness of our paradigm in inducing different levels of affect and provides an indication of features of brain activity containing discriminative information, a proposal that warrants further investigation in a larger cohort of participants.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127010772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038444
S. Gordon, Matthew Jaswa, Amelia J. Solon, Vernon J. Lawhern
{"title":"Real World BCI: Cross-Domain Learning and Practical Applications","authors":"S. Gordon, Matthew Jaswa, Amelia J. Solon, Vernon J. Lawhern","doi":"10.1145/3038439.3038444","DOIUrl":"https://doi.org/10.1145/3038439.3038444","url":null,"abstract":"In order to develop real-world BCI solutions machine learning models must generalize not only to unseen users but also to unseen scenarios. In this concept paper we describe our initial investigation into Deep Learning tools to create generalized models for both cross-subject and cross-domain learning. We demonstrate our approach using two different, laboratory grade data sets to train a learning model that we then apply to a third more complex scenario. While our results indicate that cross-domain learning is possible, we also identify potential avenues for further research and development (such as disentangling spatially or temporally overlapping responses). Finally, we describe our work to implement a system that uses cross-domain learning to develop a real-time application for performing BCI-based Human-Centric Scene Analysis.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127353732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BCIforReal '17Pub Date : 2017-03-13DOI: 10.1145/3038439.3038441
A. Brouwer, A. Snelting, Matthew Jaswa, Oded M. Flascher, L. R. Krol, T. Zander
{"title":"Physiological Effects of Adaptive Cruise Control Behaviour in Real Driving","authors":"A. Brouwer, A. Snelting, Matthew Jaswa, Oded M. Flascher, L. R. Krol, T. Zander","doi":"10.1145/3038439.3038441","DOIUrl":"https://doi.org/10.1145/3038439.3038441","url":null,"abstract":"We examined physiological responses to behavior of an Adaptive Cruise Control (ACC) system during real driving. ACC is an example of automating a task that used to be performed by the user. In order to preserve the link between the user and an automated system such that they work together optimally, physiological signals reflecting mental state may be useful. We asked 15 participants to use an ACC at designated times while driving a track. When the ACC was activated, the car decelerated either strongly or softly, which was either according to expectation or not. Heart rate, eye blinks, and brain signals (EEG) were recorded. Heart rate and blink duration were the same following the announcement of an upcoming expected or unexpected deceleration profile. Heart rate and blink duration increased when a strong compared to a soft deceleration profile was announced, consistent with a state of arousal or startle. This was only found for the first half of the trials, when the driver was expected to be more alert and engaged (as also evidenced by decreasing heart rate, and increasing EEG alpha and blink duration over the trials). We conclude that for ACC behavior that is relevant for the driver, heart rate and blink duration may be used as a source of information about mental state elicited by the ACC, which could be used to evaluate driving experience.","PeriodicalId":285683,"journal":{"name":"BCIforReal '17","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130894532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}