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A multimodal sensor fusion platform for objective assessment of motor states in Parkinson's disease
Örebro universitet, Handelshögskolan vid Örebro Universitet.ORCID-id: 0000-0002-2372-4226
th Computer Engineering, Dalarna University, Sweden.
Department of Pharmacology, Gothenburg University, Sweden.
Department of Neuroscience, Uppsala University, Sweden (.
Vise andre og tillknytning
2019 (engelsk)Inngår i: IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI 19), 2019Konferansepaper, Oral presentation with published abstract (Fagfellevurdert)
Abstract [en]

This study proposes a platform to objectively assess motor states in Parkinson’s disease (PD) using sensor technology and machine learning. The platform uses sensor information gathered during standardized motor tasks and fuses them in a data-driven manner to produce an index representing motor states of the patients. After investigating clinimetric properties of the platform it was found that the platform had good validity and responsiveness to treatment, which are essential for developing systems to individualize treatments.

sted, utgiver, år, opplag, sider
2019.
HSV kategori
Forskningsprogram
Informatik
Identifikatorer
URN: urn:nbn:se:oru:diva-74621OAI: oai:DiVA.org:oru-74621DiVA, id: diva2:1321122
Konferanse
IEEE Conference on Biomedical and Health Informatics 2019, Chicago, IL, USA, 19-22 May, 2019
Forskningsfinansiär
Knowledge FoundationTilgjengelig fra: 2019-06-07 Laget: 2019-06-07 Sist oppdatert: 2019-06-10bibliografisk kontrollert

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A multimodal sensor fusion platform for objective assessment of motor states in Parkinson’s disease(170 kB)15 nedlastinger
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