BioFidget: biofeedback for respiration training using an augmented fidget spinner

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaties (Scopus)

Uittreksel

This paper presents BioFidget, a biofeedback system that integrates physiological sensing and display into a smart fidget spinner for respiration training. We present a simple yet novel hardware design that transforms a fidget spinner into 1) a nonintrusive heart rate variability (HRV) sensor, 2) an electromechanical respiration sensor, and 3) an information display. The combination of these features enables users to engage in respiration training through designed tangible and embodied interactions, without requiring them to wear additional physiological sensors. The results of this empirical user study prove that the respiration training method reduces stress, and the proposed system meets the requirements of sensing validity and engagement with 32 participants in a practical setting.

TaalEngels
TitelProceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Subtitel(CHI '18)
Plaats van productieNew York, NY, USA
UitgeverijAssociation for Computing Machinery, Inc
Aantal pagina's12
ISBN van geprinte versie9781450356206
DOI's
StatusGepubliceerd - 20 apr 2018
EvenementCHI '18 - Montreal, Canada, Montreal, Canada
Duur: 21 apr 201826 apr 2018
Congresnummer: 36
http://chi2018.acm.org
https://chi2018.acm.org/

Congres

CongresCHI '18
Verkorte titelCHI
LandCanada
StadMontreal
Periode21/04/1826/04/18
Internet adres

Vingerafdruk

Biofeedback
Sensors
Display devices
Wear of materials
Hardware

Trefwoorden

    Citeer dit

    Liang, R. H., Yu, B., Xue, M., Hu, J., & Feijs, L. M. G. (2018). BioFidget: biofeedback for respiration training using an augmented fidget spinner. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: (CHI '18) [613] New York, NY, USA: Association for Computing Machinery, Inc. DOI: 10.1145/3173574.3174187
    Liang, Rong Hao ; Yu, Bin ; Xue, Mengru ; Hu, Jun ; Feijs, Loe M.G./ BioFidget: biofeedback for respiration training using an augmented fidget spinner. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: (CHI '18). New York, NY, USA : Association for Computing Machinery, Inc, 2018.
    @inproceedings{492d03c3aa764bfaba767b7e79c6976d,
    title = "BioFidget: biofeedback for respiration training using an augmented fidget spinner",
    abstract = "This paper presents BioFidget, a biofeedback system that integrates physiological sensing and display into a smart fidget spinner for respiration training. We present a simple yet novel hardware design that transforms a fidget spinner into 1) a nonintrusive heart rate variability (HRV) sensor, 2) an electromechanical respiration sensor, and 3) an information display. The combination of these features enables users to engage in respiration training through designed tangible and embodied interactions, without requiring them to wear additional physiological sensors. The results of this empirical user study prove that the respiration training method reduces stress, and the proposed system meets the requirements of sensing validity and engagement with 32 participants in a practical setting.",
    keywords = "Biofeedback, Fidget spinner, Physiological sensing, Respiration training, Stress, Tangible interaction",
    author = "Liang, {Rong Hao} and Bin Yu and Mengru Xue and Jun Hu and Feijs, {Loe M.G.}",
    year = "2018",
    month = "4",
    day = "20",
    doi = "10.1145/3173574.3174187",
    language = "English",
    isbn = "9781450356206",
    booktitle = "Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems",
    publisher = "Association for Computing Machinery, Inc",
    address = "United States",

    }

    Liang, RH, Yu, B, Xue, M, Hu, J & Feijs, LMG 2018, BioFidget: biofeedback for respiration training using an augmented fidget spinner. in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: (CHI '18)., 613, Association for Computing Machinery, Inc, New York, NY, USA, CHI '18, Montreal, Canada, 21/04/18. DOI: 10.1145/3173574.3174187

    BioFidget: biofeedback for respiration training using an augmented fidget spinner. / Liang, Rong Hao; Yu, Bin; Xue, Mengru; Hu, Jun; Feijs, Loe M.G.

    Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: (CHI '18). New York, NY, USA : Association for Computing Machinery, Inc, 2018. 613.

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    TY - GEN

    T1 - BioFidget: biofeedback for respiration training using an augmented fidget spinner

    AU - Liang,Rong Hao

    AU - Yu,Bin

    AU - Xue,Mengru

    AU - Hu,Jun

    AU - Feijs,Loe M.G.

    PY - 2018/4/20

    Y1 - 2018/4/20

    N2 - This paper presents BioFidget, a biofeedback system that integrates physiological sensing and display into a smart fidget spinner for respiration training. We present a simple yet novel hardware design that transforms a fidget spinner into 1) a nonintrusive heart rate variability (HRV) sensor, 2) an electromechanical respiration sensor, and 3) an information display. The combination of these features enables users to engage in respiration training through designed tangible and embodied interactions, without requiring them to wear additional physiological sensors. The results of this empirical user study prove that the respiration training method reduces stress, and the proposed system meets the requirements of sensing validity and engagement with 32 participants in a practical setting.

    AB - This paper presents BioFidget, a biofeedback system that integrates physiological sensing and display into a smart fidget spinner for respiration training. We present a simple yet novel hardware design that transforms a fidget spinner into 1) a nonintrusive heart rate variability (HRV) sensor, 2) an electromechanical respiration sensor, and 3) an information display. The combination of these features enables users to engage in respiration training through designed tangible and embodied interactions, without requiring them to wear additional physiological sensors. The results of this empirical user study prove that the respiration training method reduces stress, and the proposed system meets the requirements of sensing validity and engagement with 32 participants in a practical setting.

    KW - Biofeedback

    KW - Fidget spinner

    KW - Physiological sensing

    KW - Respiration training

    KW - Stress

    KW - Tangible interaction

    UR - http://www.scopus.com/inward/record.url?scp=85046936817&partnerID=8YFLogxK

    U2 - 10.1145/3173574.3174187

    DO - 10.1145/3173574.3174187

    M3 - Conference contribution

    SN - 9781450356206

    BT - Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

    PB - Association for Computing Machinery, Inc

    CY - New York, NY, USA

    ER -

    Liang RH, Yu B, Xue M, Hu J, Feijs LMG. BioFidget: biofeedback for respiration training using an augmented fidget spinner. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: (CHI '18). New York, NY, USA: Association for Computing Machinery, Inc. 2018. 613. Beschikbaar vanaf, DOI: 10.1145/3173574.3174187