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dc.contributor.authorTakac, Boris
dc.contributor.authorCatalà Mallofré, Andreu
dc.contributor.authorRodríguez Martín, Daniel Manuel
dc.contributor.authorVan Der Aa, Nico
dc.contributor.authorChen, Wei
dc.contributor.authorRauterberg, Mattias
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2013-12-05T13:03:44Z
dc.date.created2013-07
dc.date.issued2013-07
dc.identifier.citationTakac, B. [et al.]. Position and orientation tracking in a ubiquitous monitoring system for Parkinson disease patients with freezing of gait symptom. "JMIR mhealth and uhealth", Juliol 2013, vol. 15, núm. 7.
dc.identifier.issn2291-5222
dc.identifier.urihttp://hdl.handle.net/2117/20928
dc.description.abstractBackground: Freezing of gait (FoG) is one of the most disturbing and least understood symptoms in Parkinson disease (PD). Although the majority of existing assistive systems assume accurate detections of FoG episodes, the detection itself is still an open problem. The specificity of FoG is its dependency on the context of a patient, such as the current location or activity. Knowing the patient's context might improve FoG detection. One of the main technical challenges that needs to be solved in order to start using contextual information for FoG detection is accurate estimation of the patient's position and orientation toward key elements of his or her indoor environment. Objective: The objectives of this paper are to (1) present the concept of the monitoring system, based on wearable and ambient sensors, which is designed to detect FoG using the spatial context of the user, (2) establish a set of requirements for the application of position and orientation tracking in FoG detection, (3) evaluate the accuracy of the position estimation for the tracking system, and (4) evaluate two different methods for human orientation estimation. Methods: We developed a prototype system to localize humans and track their orientation, as an important prerequisite for a context-based FoG monitoring system. To setup the system for experiments with real PD patients, the accuracy of the position and orientation tracking was assessed under laboratory conditions in 12 participants. To collect the data, the participants were asked to wear a smartphone, with and without known orientation around the waist, while walking over a predefined path in the marked area captured by two Kinect cameras with non-overlapping fields of view. Results: We used the root mean square error (RMSE) as the main performance measure. The vision based position tracking algorithm achieved RMSE = 0.16 m in position estimation for upright standing people. ..
dc.language.isoeng
dc.publisherJMIR
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshParkinson Disease, Symptomatic
dc.subject.otherContext-aware system Freezing of Gait Indoor localization Parkinson disease Person orientation
dc.titlePosition and orientation tracking in a ubiquitous monitoring system for Parkinson disease patients with freezing of gait symptom
dc.typeArticle
dc.subject.lemacParkinson, Malaltia de -- Pacients -- Rehabilitació
dc.contributor.groupUniversitat Politècnica de Catalunya. GREC - Grup de Recerca en Enginyeria del Coneixement
dc.identifier.doi10.2196/mhealth.2539
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
drac.iddocument12796916
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorTakac, B.; Catala, A.; Rodriguez, D.; Van Der Aa, N.; Chen, W.; Rauterberg, M.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameJMIR mhealth and uhealth
upcommons.citation.volume15
upcommons.citation.number7
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