Affective Brain-Computer Interfaces (aBCI 2011)

C. Mühl, Antinus Nijholt, Brandan Allison, Stephen Dunne, Dirk K.J. Heylen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    3 Citations (Scopus)

    Abstract

    Recently, many groups (see Zander and Kothe. Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general. J. Neural Eng., 8, 2011) have worked toward expanding brain-computer interface (BCI) systems to include not only active control, but also passive mental state monitoring to enhance human computer interaction (HCI). Many studies have shown that brain imaging technologies can reveal information about the affective and cognitive state of a subject, and that the interaction between humans and machines can be aided by the recognition of those user states. New developments including practical sensors, new machine learning software, and improved interaction with the HCI community are leading us to systems that seamlessly integrate passively recorded information to improve interactions with the outside world. To achieve robust passive BCIs, efforts from applied and basic sciences have to be combined. On the one hand, applied fields such as affective computing aim to develop applications that adapt to changes in the user states and thereby enrich interaction, leading to a more natural and effective usability. On the other hand, basic research in neuroscience advances our understanding of the neural processes associated with emotions. Similar advancements are made for more cognitive mental states such as attention, workload, or fatigue.
    Original languageUndefined
    Title of host publicationProceedings 4th International Conference on Affective Computing and Intelligent Interaction (ACII2011), Part II
    EditorsSidney D' Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin
    Place of PublicationBerlin
    PublisherSpringer
    Pages435
    Number of pages1
    ISBN (Print)978-3-642-24570-1
    DOIs
    Publication statusPublished - 10 Oct 2011
    Event4th International Conference on Affective Computing and Intelligent Interaction, ASCII 2011 - Memphis, United States
    Duration: 9 Oct 201112 Oct 2011
    Conference number: 4

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    Volume6975
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference4th International Conference on Affective Computing and Intelligent Interaction, ASCII 2011
    Abbreviated titleASCII
    CountryUnited States
    CityMemphis
    Period9/10/1112/10/11

    Keywords

    • METIS-279197
    • Mood
    • Affective Computing
    • Affective brain-computer interfacing
    • IR-78301
    • passive brain-computer interfacing
    • HMI-MI: MULTIMODAL INTERACTIONS
    • adaptive interfaces
    • Emotions
    • EWI-20671
    • mental state
    • user state
    • cognitive state estimation
    • EEG

    Cite this

    Mühl, C., Nijholt, A., Allison, B., Dunne, S., & Heylen, D. K. J. (2011). Affective Brain-Computer Interfaces (aBCI 2011). In S. D' Mello, A. Graesser, B. Schuller, & J-C. Martin (Eds.), Proceedings 4th International Conference on Affective Computing and Intelligent Interaction (ACII2011), Part II (pp. 435). (Lecture Notes in Computer Science; Vol. 6975). Berlin: Springer. https://doi.org/10.1007/978-3-642-24571-8_55
    Mühl, C. ; Nijholt, Antinus ; Allison, Brandan ; Dunne, Stephen ; Heylen, Dirk K.J. / Affective Brain-Computer Interfaces (aBCI 2011). Proceedings 4th International Conference on Affective Computing and Intelligent Interaction (ACII2011), Part II. editor / Sidney D' Mello ; Arthur Graesser ; Björn Schuller ; Jean-Claude Martin. Berlin : Springer, 2011. pp. 435 (Lecture Notes in Computer Science).
    @inproceedings{9d9eaf1bbb914a05938b229e484b276a,
    title = "Affective Brain-Computer Interfaces (aBCI 2011)",
    abstract = "Recently, many groups (see Zander and Kothe. Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general. J. Neural Eng., 8, 2011) have worked toward expanding brain-computer interface (BCI) systems to include not only active control, but also passive mental state monitoring to enhance human computer interaction (HCI). Many studies have shown that brain imaging technologies can reveal information about the affective and cognitive state of a subject, and that the interaction between humans and machines can be aided by the recognition of those user states. New developments including practical sensors, new machine learning software, and improved interaction with the HCI community are leading us to systems that seamlessly integrate passively recorded information to improve interactions with the outside world. To achieve robust passive BCIs, efforts from applied and basic sciences have to be combined. On the one hand, applied fields such as affective computing aim to develop applications that adapt to changes in the user states and thereby enrich interaction, leading to a more natural and effective usability. On the other hand, basic research in neuroscience advances our understanding of the neural processes associated with emotions. Similar advancements are made for more cognitive mental states such as attention, workload, or fatigue.",
    keywords = "METIS-279197, Mood, Affective Computing, Affective brain-computer interfacing, IR-78301, passive brain-computer interfacing, HMI-MI: MULTIMODAL INTERACTIONS, adaptive interfaces, Emotions, EWI-20671, mental state, user state, cognitive state estimation, EEG",
    author = "C. M{\"u}hl and Antinus Nijholt and Brandan Allison and Stephen Dunne and Heylen, {Dirk K.J.}",
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    Mühl, C, Nijholt, A, Allison, B, Dunne, S & Heylen, DKJ 2011, Affective Brain-Computer Interfaces (aBCI 2011). in S D' Mello, A Graesser, B Schuller & J-C Martin (eds), Proceedings 4th International Conference on Affective Computing and Intelligent Interaction (ACII2011), Part II. Lecture Notes in Computer Science, vol. 6975, Springer, Berlin, pp. 435, 4th International Conference on Affective Computing and Intelligent Interaction, ASCII 2011, Memphis, United States, 9/10/11. https://doi.org/10.1007/978-3-642-24571-8_55

    Affective Brain-Computer Interfaces (aBCI 2011). / Mühl, C.; Nijholt, Antinus; Allison, Brandan; Dunne, Stephen; Heylen, Dirk K.J.

    Proceedings 4th International Conference on Affective Computing and Intelligent Interaction (ACII2011), Part II. ed. / Sidney D' Mello; Arthur Graesser; Björn Schuller; Jean-Claude Martin. Berlin : Springer, 2011. p. 435 (Lecture Notes in Computer Science; Vol. 6975).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    TY - GEN

    T1 - Affective Brain-Computer Interfaces (aBCI 2011)

    AU - Mühl, C.

    AU - Nijholt, Antinus

    AU - Allison, Brandan

    AU - Dunne, Stephen

    AU - Heylen, Dirk K.J.

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    N2 - Recently, many groups (see Zander and Kothe. Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general. J. Neural Eng., 8, 2011) have worked toward expanding brain-computer interface (BCI) systems to include not only active control, but also passive mental state monitoring to enhance human computer interaction (HCI). Many studies have shown that brain imaging technologies can reveal information about the affective and cognitive state of a subject, and that the interaction between humans and machines can be aided by the recognition of those user states. New developments including practical sensors, new machine learning software, and improved interaction with the HCI community are leading us to systems that seamlessly integrate passively recorded information to improve interactions with the outside world. To achieve robust passive BCIs, efforts from applied and basic sciences have to be combined. On the one hand, applied fields such as affective computing aim to develop applications that adapt to changes in the user states and thereby enrich interaction, leading to a more natural and effective usability. On the other hand, basic research in neuroscience advances our understanding of the neural processes associated with emotions. Similar advancements are made for more cognitive mental states such as attention, workload, or fatigue.

    AB - Recently, many groups (see Zander and Kothe. Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general. J. Neural Eng., 8, 2011) have worked toward expanding brain-computer interface (BCI) systems to include not only active control, but also passive mental state monitoring to enhance human computer interaction (HCI). Many studies have shown that brain imaging technologies can reveal information about the affective and cognitive state of a subject, and that the interaction between humans and machines can be aided by the recognition of those user states. New developments including practical sensors, new machine learning software, and improved interaction with the HCI community are leading us to systems that seamlessly integrate passively recorded information to improve interactions with the outside world. To achieve robust passive BCIs, efforts from applied and basic sciences have to be combined. On the one hand, applied fields such as affective computing aim to develop applications that adapt to changes in the user states and thereby enrich interaction, leading to a more natural and effective usability. On the other hand, basic research in neuroscience advances our understanding of the neural processes associated with emotions. Similar advancements are made for more cognitive mental states such as attention, workload, or fatigue.

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    KW - adaptive interfaces

    KW - Emotions

    KW - EWI-20671

    KW - mental state

    KW - user state

    KW - cognitive state estimation

    KW - EEG

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    Mühl C, Nijholt A, Allison B, Dunne S, Heylen DKJ. Affective Brain-Computer Interfaces (aBCI 2011). In D' Mello S, Graesser A, Schuller B, Martin J-C, editors, Proceedings 4th International Conference on Affective Computing and Intelligent Interaction (ACII2011), Part II. Berlin: Springer. 2011. p. 435. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-24571-8_55