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dc.contributor.authorRodríguez Martín, Daniel Manuel
dc.contributor.authorPérez López, Carlos
dc.contributor.authorSamà Monsonís, Albert
dc.contributor.authorCabestany Moncusí, Joan
dc.contributor.authorCatalà Mallofré, Andreu
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.date.accessioned2013-11-14T15:02:57Z
dc.date.available2013-11-14T15:02:57Z
dc.date.created2013-10-18
dc.date.issued2013-10-18
dc.identifier.citationRodriguez, D. [et al.]. A wearable inertial measurement unit for long-term monitoring in the dependency care area. "Sensors", 18 Octubre 2013, vol. 13, núm. 10, p. 14079-14104.
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2117/20612
dc.description.abstractHuman movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU’s movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A μSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson’s disease symptoms, in gait analysis, and in a fall detection system
dc.format.extent26 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshParkinson Disease -- diagnosis
dc.subject.lcshPersonal health device
dc.subject.lcshManagement and assessment of the disease
dc.titleA wearable inertial measurement unit for long-term monitoring in the dependency care area
dc.typeArticle
dc.subject.lemacParkinson, Malaltia de
dc.contributor.groupUniversitat Politècnica de Catalunya. GREC - Grup de Recerca en Enginyeria del Coneixement
dc.contributor.groupUniversitat Politècnica de Catalunya. AHA - Arquitectures Hardware Avançades
dc.identifier.doi10.3390/s131014079
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.mdpi.com/1424-8220/13/10/14079/pdf¿
dc.rights.accessOpen Access
local.identifier.drac12880005
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.authorRodriguez, D.; Perez, C.; Sama, A.; Cabestany, J.; Catala, A.
local.citation.publicationNameSensors
local.citation.volume13
local.citation.number10
local.citation.startingPage14079
local.citation.endingPage14104
dc.identifier.pmid24145917


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