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dc.contributor.authorRodríguez Molinero, Alejandro
dc.contributor.authorSamà Monsonís, Albert
dc.contributor.authorPérez López, Carlos
dc.contributor.authorRodríguez Martín, Daniel Manuel
dc.contributor.authorAlcaine, Sheila
dc.contributor.authorMestre, Berta
dc.contributor.authorQuispe, Paola
dc.contributor.authorGiuliani, Benedetta
dc.contributor.authorVainstein, Gabriel
dc.contributor.authorBrowne, Patrick
dc.contributor.authorSweeney, Dean
dc.contributor.authorMoreno Aróstegui, Juan Manuel
dc.contributor.authorBayés, Àngels
dc.contributor.authorLewy, Hadas
dc.contributor.authorCosta, Alberto
dc.contributor.authorAnnicchiarico, Roberta
dc.contributor.authorCounihan, Timothy
dc.contributor.authorÓLaighin, Gearóid
dc.contributor.authorCabestany Moncusí, Joan
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.identifier.citationRodríguez, A., Sama, A., Perez, C., Rodriguez-Martin, D., Alcaine, S., Mestre, B., Quispe, P., Giuliani, B., Vainstein, G., Browne, P., Sweeney, D., Moreno, J., Bayés, À., Lewy, H., Costa, A., Annicchiarico, R., Counihan, T., ÓLaighin, G., Cabestany, J. Analysis of correlation between an accelerometer-Based algorithm for Detecting Parkinsonian gait and UPDRS subscales. "Frontiers in Neurology", 1 Setembre 2017, vol. 8, p. 1-6.
dc.description.abstractBackground: Our group earlier developed a small monitoring device, which uses accelerometer measurements to accurately detect motor fluctuations in patients with Parkinson’s (On and Off state) based on an algorithm that characterizes gait through the frequency content of strides. To further validate the algorithm, we studied the correlation of its outputs with the motor section of the Unified Parkinson’s Disease Rating Scale part-III (UPDRS-III). Method: Seventy-five patients suffering from Parkinson’s disease were asked to walk both in the Off and the On state while wearing the inertial sensor on the waist. Additionally, all patients were administered the motor section of the UPDRS in both motor phases. Tests were conducted at the patient’s home. Convergence between the algorithm and the scale was evaluated by using the Spearman’s correlation coefficient. results: Correlation with the UPDRS-III was moderate (rho -0.56; p < 0.001). Correlation between the algorithm outputs and the gait item in the UPDRS-III was good (rho -0.73; p < 0.001). The factorial analysis of the UPDRS-III has repeatedly shown that several of its items can be clustered under the so-called Factor 1: “axial function, balance, and gait.” The correlation between the algorithm outputs and this factor of the UPDRS-III was -0.67 (p < 0.01). conclusion: The correlation achieved by the algorithm with the UPDRS-III scale suggests that this algorithm might be a useful tool for monitoring patients with Parkinson’s disease and motor fluctuations.
dc.format.extent6 p.
dc.rightsAttribution 3.0 Spain
dc.subjectÀrees temàtiques de la UPC::Ciències de la salut
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica
dc.subjectÀrees temàtiques de la UPC::Enginyeria electrònica
dc.subject.lcshParkinson's disease -- Research
dc.subject.lcshInertial sensors
dc.subject.otherObjective monitoring
dc.subject.otherParkinson's disease
dc.titleAnalysis of correlation between an accelerometer-Based algorithm for Detecting Parkinsonian gait and UPDRS subscales
dc.subject.lemacParkinson, Malaltia de
dc.contributor.groupUniversitat Politècnica de Catalunya. CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/287677/EU/Personal Health Device for the Remote and Autonomous Management of Parkinson’s Disease/REMPARK
local.citation.authorRodríguez, A.; Sama, A.; Perez, C.; Rodriguez-Martin, D.; Alcaine, S.; Mestre, B.; Quispe, P.; Giuliani, B.; Vainstein, G.; Browne, P.; Sweeney, D.; Moreno, J.; Bayés, À.; Lewy, H.; Costa, A.; Annicchiarico, R.; Counihan, T.; ÓLaighin, G.; Cabestany, J.
local.citation.publicationNameFrontiers in Neurology

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Attribution 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution 3.0 Spain