Publication:
Assessing walking strategies using insole pressure sensors for stroke survivors

dc.affiliation.dptoUC3M. Departamento de Ingeniería Telemáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Aplicaciones y Servicios Telemáticos (GAST)es
dc.contributor.authorMuñoz Organero, Mario
dc.contributor.authorParker, Jack
dc.contributor.authorPowell, Lauren
dc.contributor.authorMawson, Susan
dc.date.accessioned2018-02-22T15:57:48Z
dc.date.available2018-02-22T15:57:48Z
dc.date.issued2016-10-01
dc.description.abstractInsole pressure sensors capture the different forces exercised over the different parts of the sole when performing tasks standing up such as walking. Using data analysis and machine learning techniques, common patterns and strategies from different users to achieve different tasks can be automatically extracted. In this paper, we present the results obtained for the automatic detection of different strategies used by stroke survivors when walking as integrated into an Information Communication Technology (ICT) enhanced Personalised Self-Management Rehabilitation System (PSMrS) for stroke rehabilitation. Fourteen stroke survivors and 10 healthy controls have participated in the experiment by walking six times a distance from chair to chair of approximately 10 m long. The Rivermead Mobility Index was used to assess the functional ability of each individual in the stroke survivor group. Several walking strategies are studied based on data gathered from insole pressure sensors and patterns found in stroke survivor patients are compared with average patterns found in healthy control users. A mechanism to automatically estimate a mobility index based on the similarity of the pressure patterns to a stereotyped stride is also used. Both data gathered from stroke survivors and healthy controls are used to evaluate the proposed mechanisms. The output of trained algorithms is applied to the PSMrS system to provide feedback on gait quality enabling stroke survivors to self-manage their rehabilitation.en
dc.description.sponsorshipThe research leading to these results has received funding from the “HERMES-SMART DRIVER” project TIN2013-46801-C4-2-R funded by the Spanish MINECO, from the grant PRX15/00036 from the Ministerio de Educación Cultura y Deporte. The research was also funded and supported by the NIHR CLAHRC Yorkshire and Humber.en
dc.format.extent18
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationMunoz-Organero, M., Parker, J., Powell, L., Mawson, S. (2016). Assessing Walking Strategies Using Insole Pressure Sensors for Stroke Survivors. Sensors, 16 (10), 1631.
dc.identifier.doihttps://doi.org/10.3390/s16101631
dc.identifier.issn1424-8220
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue10 (1631)
dc.identifier.publicationlastpage18
dc.identifier.publicationtitleSensorsen
dc.identifier.publicationvolume16
dc.identifier.urihttps://hdl.handle.net/10016/25573
dc.identifier.uxxiAR/0000018378
dc.language.isoeng
dc.publisherMDPI (Multidisciplinary Digital Publishing Institute)
dc.relation.projectIDGobierno de España. TIN2013-46801-C4-2-R
dc.relation.projectIDGobierno de España. PRX15/00036
dc.rights© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/)
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherInsole pressure sensorsen
dc.subject.otherStroke survivalsen
dc.subject.otherMachine learningen
dc.subject.otherRehabilitationen
dc.subject.otherWalking strategiesen
dc.subject.otherSelf-managementen
dc.subject.otherChronic diseaseen
dc.subject.otherRecoveryen
dc.subject.otherPlasticityen
dc.titleAssessing walking strategies using insole pressure sensors for stroke survivorsen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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