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A wearable inertial measurement unit for long-term monitoring in the dependency care area
dc.contributor.author | Rodríguez Martín, Daniel Manuel |
dc.contributor.author | Pérez López, Carlos |
dc.contributor.author | Samà Monsonís, Albert |
dc.contributor.author | Cabestany Moncusí, Joan |
dc.contributor.author | Català Mallofré, Andreu |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2013-11-14T15:02:57Z |
dc.date.available | 2013-11-14T15:02:57Z |
dc.date.created | 2013-10-18 |
dc.date.issued | 2013-10-18 |
dc.identifier.citation | Rodriguez, 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.issn | 1424-8220 |
dc.identifier.uri | http://hdl.handle.net/2117/20612 |
dc.description.abstract | Human 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.extent | 26 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
dc.subject.lcsh | Parkinson Disease -- diagnosis |
dc.subject.lcsh | Personal health device |
dc.subject.lcsh | Management and assessment of the disease |
dc.title | A wearable inertial measurement unit for long-term monitoring in the dependency care area |
dc.type | Article |
dc.subject.lemac | Parkinson, Malaltia de |
dc.contributor.group | Universitat Politècnica de Catalunya. GREC - Grup de Recerca en Enginyeria del Coneixement |
dc.contributor.group | Universitat Politècnica de Catalunya. AHA - Arquitectures Hardware Avançades |
dc.identifier.doi | 10.3390/s131014079 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.mdpi.com/1424-8220/13/10/14079/pdf¿ |
dc.rights.access | Open Access |
local.identifier.drac | 12880005 |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/FP7/287677/EU/Personal Health Device for the Remote and Autonomous Management of Parkinson’s Disease/REMPARK |
local.citation.author | Rodriguez, D.; Perez, C.; Sama, A.; Cabestany, J.; Catala, A. |
local.citation.publicationName | Sensors |
local.citation.volume | 13 |
local.citation.number | 10 |
local.citation.startingPage | 14079 |
local.citation.endingPage | 14104 |
dc.identifier.pmid | 24145917 |
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