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Automatic recognition of pain, anxiety, engagement and tiredness for virtual rehabilitation from stroke: A marginalization approach

Rivas, JJ; Palafox, L; Hernadex-Franco, J; Del Carmen Lara, M; Berthouze, NL; Orihela-Espina, F; Sucar, LE; (2018) Automatic recognition of pain, anxiety, engagement and tiredness for virtual rehabilitation from stroke: A marginalization approach. In: Proceedings of the 2017 Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). (pp. pp. 159-164). IEEE: San Antonio, TX, USA. Green open access

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Abstract

Virtual rehabilitation taps affective computing to personalize therapy. States of anxiety, pain and engagement (affective) and tiredness (physical or psychological) were studied to be inferable from metrics of 3D hand location-proxy of hand movement- and fingers' pressure relevant for upper limb motor recovery. Features from the data streams characterized the motor dynamics of 2 stroke patients attending 10 sessions of motor virtual rehabilitation. Experts tagged states manifestations from videos. We aid classification contributing with a marginalization mechanism whereby absent input is reconstructed. With the hand movement information absent, marginalization statistically outperformed a base model where such input is ignored. Marginalized classification performance was (Area below ROC curve: μ ± σ) 0.880 ± 0.173 and 0.738 ± 0.177 for each patient. Marginalization aid classification sustaining performance under input failure or permitting different sensing settings.

Type: Proceedings paper
Title: Automatic recognition of pain, anxiety, engagement and tiredness for virtual rehabilitation from stroke: A marginalization approach
Event: 2017 Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
Location: San Antonio, Texas, United States
Dates: 23 October 2017 - 26 October 2017
ISBN-13: 978-1-5386-0680-3
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ACIIW.2017.8272607
Publisher version: https://doi.org/10.1109/ACIIW.2017.8272607
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Multimodal systems; marginalization; virtual rehabilitation; stroke; probabilistic graphical models.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > UCL Interaction Centre
URI: https://discovery.ucl.ac.uk/id/eprint/1571089
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