Virtual rehabilitation supports motor training following stroke by means of tailored virtual environments. To optimize therapy outcome, virtual rehabilitation systems automatically adapt to the different patients' changing needs. Adaptation decisions should ideally be guided by both the observable performance and the hidden mind state of the user. We hypothesize that some affective aspects can be inferred from observable metrics. Here we present preliminary results of a classification exercise to decide on 4 states; tiredness, tension, pain and satisfaction. Descriptors of 3D hand movement and finger pressure were collected from 2 post-stroke participants while they practice on a virtual rehabilitation platform. Linear Support Vector Machine models were learnt to unfold a predictive relation between observation and the affective states considered. Initial results are promising (ROC Area under the curve (mean±std): 0.713 ± 0.137). Confirmation of these opens the door to incorporate surrogates of mind state into the algorithm deciding on therapy adaptation.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Detecting affective states in virtual rehabilitation



    Erscheinungsdatum :

    2015-05-23


    Anmerkungen:

    In: Arnrich, B and Ersoy, C and Dey, A and Berthouze, N, (eds.) Proceedings of 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth). (pp. pp. 287-292). IEEE: Istanbul, Turkey. (2015)


    Medientyp :

    Paper


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629



    Automatic Recognition of Multiple Affective States in Virtual Rehabilitation by Exploiting the Dependency Relationships

    Rivas, JJ / Orihuela-Espina, F / Sucar Succar, LE et al. | BASE | 2019

    Freier Zugriff

    Unobtrusive Inference of Affective States in Virtual Rehabilitation from Upper Limb Motions: A Feasibility Study

    Rivas, JJ / Orihuela-Espina, F / Palafox, L et al. | BASE | 2018

    Freier Zugriff

    Virtual Rehabilitation

    Bayón-Calatayud, Manuel / Peri, Elisabetta / Nistal, Francisco Fernández et al. | Springer Verlag | 2015


    Affective states and adaptation to parabolic flights

    Collado, Aurélie / Langlet, Cécile / Tzanova, Tzvetomira et al. | Elsevier | 2017


    Affective states and adaptation to parabolic flights

    Collado, Aurélie | Online Contents | 2017