<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-19T18:17:32Z</responseDate><request verb="GetRecord" identifier="oai:riubu.ubu.es:10259/7536" metadataPrefix="mods">https://riubu.ubu.es/oai/request</request><GetRecord><record><header><identifier>oai:riubu.ubu.es:10259/7536</identifier><datestamp>2023-04-18T10:42:52Z</datestamp><setSpec>com_10259_4141</setSpec><setSpec>com_10259_5086</setSpec><setSpec>com_10259_2604</setSpec><setSpec>com_10259_4219</setSpec><setSpec>com_10259_4996</setSpec><setSpec>com_10259_3989</setSpec><setSpec>com_10259.4_106</setSpec><setSpec>com_10259_5377</setSpec><setSpec>com_10259_6688</setSpec><setSpec>col_10259_4142</setSpec><setSpec>col_10259_4220</setSpec><setSpec>col_10259_6689</setSpec><setSpec>col_10259_4999</setSpec><setSpec>col_10259_5378</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
<mods:name>
<mods:namePart>Ramírez Sanz, José Miguel</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Garrido Labrador, José Luis</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Olivares Gil, Alicia</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>García Bustillo, Álvaro</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Arnaiz González, Álvar</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Diez Pastor, José Francisco</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Jahouh, Maha</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>González Santos, Josefa</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>González Bernal, Jerónimo</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Allende-Río, Marta</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Valiñas Sieiro, Florita</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Trejo Gabriel y Galán, José Mª</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Cubo Delgado, Esther</mods:namePart>
</mods:name>
<mods:extension>
<mods:dateAvailable encoding="iso8601">2023-03-13T12:15:33Z</mods:dateAvailable>
</mods:extension>
<mods:extension>
<mods:dateAccessioned encoding="iso8601">2023-03-13T12:15:33Z</mods:dateAccessioned>
</mods:extension>
<mods:originInfo>
<mods:dateIssued encoding="iso8601">2023-02</mods:dateIssued>
</mods:originInfo>
<mods:identifier type="uri">http://hdl.handle.net/10259/7536</mods:identifier>
<mods:identifier type="doi">10.3390/healthcare11040507</mods:identifier>
<mods:identifier type="essn">2227-9032</mods:identifier>
<mods:abstract>The consolidation of telerehabilitation for the treatment of many diseases over the last&#xd;
decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in&#xd;
remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to&#xd;
unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises&#xd;
and proper corporal movements online should also be mentioned. The focus of this paper is on&#xd;
a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and&#xd;
other less accessible locations. A full-stack is presented using big data frameworks that facilitate&#xd;
communication between the patient and the occupational therapist, the recording of each session,&#xd;
and real-time skeleton identification using artificial intelligence techniques. Big data technologies are&#xd;
used to process the numerous videos that are generated during the course of treating simultaneous&#xd;
patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for&#xd;
automated evaluation of corporal exercises, which is of immense help to the therapists in charge of&#xd;
the treatment programs.</mods:abstract>
<mods:language>
<mods:languageTerm>eng</mods:languageTerm>
</mods:language>
<mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by/4.0/</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">Atribución 4.0 Internacional</mods:accessCondition>
<mods:subject>
<mods:topic>Parkinson’s disease</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Telerehabilitation</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Telemedicine</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Big data</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Artificial intelligence in healthcare</mods:topic>
</mods:subject>
<mods:titleInfo>
<mods:title>A Low-Cost System Using a Big-Data Deep-Learning Framework for Assessing Physical Telerehabilitation: A Proof-of-Concept</mods:title>
</mods:titleInfo>
<mods:genre>info:eu-repo/semantics/article</mods:genre>
</mods:mods></metadata></record></GetRecord></OAI-PMH>