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AI-Rehab: a framework for AI driven neurorehabilitation training - the profiling challenge

2020Conference object Open access
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dc.contributor.authorFermé, Eduardo
dc.contributor.authorBermúdez i Badia, Sergi
dc.contributor.authorSirsat, Manisha
dc.contributor.authorAlmeida, Yuri
dc.date.accessioned2022-07-20T13:42:47Z
dc.date.available2022-07-20T13:42:47Z
dc.date.issued2020
dc.description.abstractOne of the health clinic challenges is rehabilitation therapy cognitive impairment that can happen after brain injury, dementia and in normal cognitive decline due to aging. Current cognitive rehabilitation therapy has been shown to be the most effective way to address this problem. However, a) it is not adaptive for every patient, b) it has a high cost, and c) it is usually implemented in clinical environments. The Task Generator (TG) is a free tool for the generation of cognitive training tasks. However, TG is not designed to adapt and monitor the cognitive progress of the patient. Hence, we propose in the BRaNT project an enhancement of TG with belief revision and machine learning techniques, gamification and remote monitoring capabilities to enable health professionals to provide a long-term personalized cognitive rehabilitation therapy at home. The BRaNT is an interdisciplinary effort that addresses scientific limitations of current practices as well as provides solutions towards the sustainability of health systems and contributes towards the improvement of quality of life of patients. This paper proposes the AI-Rehab framework for the BRaNT, explains profiling challenge in the situation of insufficient data and presents an alternate AI solutions which might be applicable once enough data is available.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAlmeida, Y., Sirsat, M. S., i Badia, S. B., & Fermé, E. (2020). AI-Rehab: a framework for AI driven neurorehabilitation training - the profiling challenge. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: Cognitive Health IT, 845-853, 2020 , Valletta, Malta.pt_PT
dc.identifier.doi10.5220/0009369108450853pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/4435
dc.language.isoengpt_PT
dc.relationNOVA Laboratory for Computer Science and Informatics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectLong term care in cognitive neurorehabilitationpt_PT
dc.subjectProfiling challengespt_PT
dc.subjectMachine learningpt_PT
dc.subjectBelief revisionpt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleAI-Rehab: a framework for AI driven neurorehabilitation training - the profiling challengept_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleNOVA Laboratory for Computer Science and Informatics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCCI-COM%2F30990%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FCEC%2F04516%2F2019/PT
oaire.citation.endPage853pt_PT
oaire.citation.startPage845pt_PT
oaire.citation.titleProceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies, Valletta, Maltapt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameFermé
person.familyNameBermúdez i Badia
person.familyNameAristides da Silva Godinho de Almeida
person.givenNameEduardo
person.givenNameSergi
person.givenNameYuri
person.identifierhttps://scholar.google.com/citations?user=Qu6aCR8AAAAJ&hl
person.identifier239789
person.identifier.ciencia-idC515-D92F-8F54
person.identifier.ciencia-idCA17-5E88-2B37
person.identifier.ciencia-id3719-8255-2B9C
person.identifier.orcid0000-0002-9618-2421
person.identifier.orcid0000-0003-4452-0414
person.identifier.orcid0000-0003-3213-7514
person.identifier.ridC-8681-2018
person.identifier.scopus-author-id6507544015
person.identifier.scopus-author-id6506360007
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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