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Third Workshop on Affective Brain-Computer Interfaces (ABCI 2013): Introduction

机译:情感脑电脑界面的第三次研讨会(ABCI 2013):介绍

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Following the first and second workshop on affective brain-computer interfaces, held in conjunction with ACII in Amsterdam (2009) and Memphis (2011), the third workshop explores the advantages and limitations of using neurophysiological signals for the automatic recognition of affective and cognitive states, and the different ways to use this information about the user in applications within the health, arts, and entertainment domains. The goal is to bring researchers, artists, and practitioners together to present state-of-the-art progress, discuss pitfalls and limitations and share and create visions, and thereby encourage the development of guidelines and frameworks for affective BCI. The contributions feature a large range of interesting topics. The most works explore the classification of affective states via different neurophysiological measurements, such as Electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI). Other works study the inclusion of additional physiological signals, such as muscular activity, electro dermal measurements, or heart rate, for the detection of emotions. In this context techniques for the identification of different electrophysiological signal sources, multimodal data fusion methods, and non-linear feature extraction approaches are discussed. Other contributions treat methodological problems, like the generalization of a (workload) classifier from the specific context in which it was trained to a more complex task and the search for suited evaluation criteria for affect classifiers. An unusual but valuable perspective is taken by works that look at the influence of affect on active BCI performance: Is the emotional state of BCI users a critical factor for their capability to control thought based interaction and if so, what can we do to put them in the optimal state? Finally, theoretical contributions elucidate the value of BCI for the arts and for industry.
机译:继艾斯特丹(2009年)和孟菲斯(2009)和孟菲斯(2011年)和孟菲斯(2011)和孟菲斯共同举行的第一和第二次研讨会之后,第三次研讨会探讨了使用神经生理信号来自动识别情感和认知状态的优点和局限性以及在健康,艺术和娱乐域内使用这些信息的不同方式使用这些信息。目标是将研究人员,艺术家和从业者共同展示了最先进的进步,讨论了陷阱和局限性,共享并创造了愿景,从而鼓励为情感BCI制定指南和框架。贡献具有大量有趣的主题。最多的作品通过不同的神经生理测量来探讨情感状态的分类,例如脑电图(EEG),功能近红外光谱(FNIR)和功能磁共振成像(FMRI)。其他作品研究了含有额外的生理信号,例如肌肉活性,电动真皮测量或心率,用于检测情绪。在这种上下文中,讨论了用于识别不同电生理信号源的技术,讨论多模式数据融合方法和非线性特征提取方法。其他贡献对待方法问题,如从特定上下文的(工作负载)分类器的泛化,其中它被训练到更复杂的任务,并且搜索适合于影响分类器的评估标准。一种不寻常但有价值的角度来看,看起来对影响积极BCI性能的影响:BCI用户的情绪状态是他们控制基于思想的互动的关键因素,如果是这样,我们可以做些什么在最佳状态?最后,理论贡献阐明了BCI为艺术和行业的价值。

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