Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ACII.2013.153 | ACII |
Keywords | Field | DocType |
neurophysiology,brain computer interfaces,emotion,affect | Functional magnetic resonance imaging,Communication,Computer science,Brain–computer interface,Sensor fusion,Feature extraction,Affective computing,Cognition,Affect (psychology),Electroencephalography | Conference |
ISSN | Citations | PageRank |
2156-8103 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Mühl | 1 | 110 | 8.44 |
| Guillaume Chanel | 2 | 640 | 45.06 |
| Brendan Allison | 3 | 202 | 19.73 |
| Anton Nijholt | 4 | 2356 | 240.31 |