Imperial College London
Dr Felipe Orihuela-Espina

DrFelipeOrihuela-Espina

Faculty of Medicine, Department of Surgery & Cancer

Honorary Lecturer
 
 
 
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Publications

Citation

BibTex format

@inproceedings{Joel:2018:10.1109/ACIIW.2017.8272607,
author = {Joel, Rivas J and Palafox, L and Hernandez-Franco, J and del, Carmen Lara M and Bianchi-Berthouze, N and Orihuela-Espina, F and Enrique, Sucar L},
doi = {10.1109/ACIIW.2017.8272607},
pages = {159--164},
publisher = {IEEE},
title = {Automatic Recognition of Pain, Anxiety, Engagement and Tiredness for Virtual Rehabilitation from Stroke: A Marginalization Approach},
url = {http://dx.doi.org/10.1109/ACIIW.2017.8272607},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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.
AU  - Joel,Rivas J
AU  - Palafox,L
AU  - Hernandez-Franco,J
AU  - del,Carmen Lara M
AU  - Bianchi-Berthouze,N
AU  - Orihuela-Espina,F
AU  - Enrique,Sucar L
DO  - 10.1109/ACIIW.2017.8272607
EP  - 164
PB  - IEEE
PY  - 2018///
SN  - 2156-8103
SP  - 159
TI  - Automatic Recognition of Pain, Anxiety, Engagement and Tiredness for Virtual Rehabilitation from Stroke: A Marginalization Approach
UR  - http://dx.doi.org/10.1109/ACIIW.2017.8272607
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000425254600031&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/58420
ER  -
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