Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/28271
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Campo DCValorIdioma
dc.contributor.authorPostolache, O.-
dc.contributor.editorMiclaus, S., Bechet, P., Munteanu, M., and Dan Milici, L.-
dc.date.accessioned2023-03-13T12:01:53Z-
dc.date.available2023-03-13T12:01:53Z-
dc.date.issued2022-
dc.identifier.citationPostolache, O. (2022). Smart sensing and AI for physical therapy in IoT era. In S. Miclaus, P. Bechet, M. Munteanu, & L. Dan Milici (Eds.), IOP Conference Series: Materials Science and Engineering (vol. 1254). IOP Publishing. https://doi.org/10.1088/1757-899X/1254/1/012006-
dc.identifier.issn1757-8981-
dc.identifier.urihttp://hdl.handle.net/10071/28271-
dc.description.abstractIt is well known that medical spending increase with disability status. Per capita spending for people with five or more limitations in activities of daily living (ADLs) is nearly five times the amount incurred by those with limitations in only one instrumental activities of daily living (IADLs). Physical therapy is the way to improve the motor capabilities however it takes a lot of time, it requires physiotherapists services, is often painful and the outcome are evaluated in subjective way. New technologies including smart sensors were adopted in healthcare including wearable solutions for cardiac and respiratory activity monitoring and successfully are contributing to reduce the costs of services. In the case of motor activity and particularly in physical rehabilitation the developments are still reduced the physical therapy services are using as hardware mechanical equipment without sensing, embedded processing and internet connectivity that significatively reduce the possibility to measure and evaluate the physical training outcomes in objective way. In this paper the disruptive solutions for physical therapy are presented that are based on hot technologies such as smart sensors, IoT, virtual reality (VR), mixed reality (MR), and artificial intelligence (AI). Applied AI may conduct to develop models, classifiers (gait classification) and short term or medium term prediction of physical therapy outcomes. Highly motivation of the patients under physical rehabilitation can be increased promoting serious game characterized by VR and MR scenarioseng
dc.language.isoeng-
dc.publisherIOP Publishing-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PT-
dc.relation.ispartofIOP Conference Series: Materials Science and Engineering-
dc.rightsopenAccess-
dc.titleSmart sensing and AI for physical therapy in IoT eraeng
dc.typeconferenceObject-
dc.event.titleInternational Conference on Electromagnetic Fields, Signals and BioMedical Engineering (ICEMS-BIOMED 2022)-
dc.event.typeConferênciapt
dc.event.locationSibiu, Romaniaeng
dc.event.date2022-
dc.peerreviewedyes-
dc.volume1254-
dc.date.updated2023-03-13T11:59:43Z-
dc.description.versioninfo:eu-repo/semantics/publishedVersion-
dc.identifier.doi10.1088/1757-899X/1254/1/012006-
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopor
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.subject.fosDomínio/Área Científica::Ciências Médicas::Ciências da Saúdepor
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-92325-
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