A heterogeneous database for movement knowledge extraction in Parkinson's disease
View/Open
Cita com:
hdl:2117/22465
Document typeConference lecture
Defense date2013
Rights accessOpen Access
Except where otherwise noted, content on this work
is licensed under a Creative Commons license
:
Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
This paper presents the design and methodology used to create a heterogeneous database for knowledge movement extraction in
Parkinson's Disease. This database is being constructed as part of REM-
PARK project and is composed of movement measurements acquired from
inertial sensors, standard medical scales as Uni ed Parkinson's Disease
Rating Scale, and other information obtained from 90 Parkinson's Disease
patients. The signals obtained will be used to create movement disorder
detection algorithms using supervised learning techniques. The different
sources of information and the need of labelled data pose many challenges which the methodology described in this paper addresses. Some preliminary data obtained are presented.
CitationSama, A. [et al.]. A heterogeneous database for movement knowledge extraction in Parkinson's disease. A: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. "ESANN 2013 proceedings: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Bruges (Belgium), 24-26 April 2013". Bruges: 2013, p. 413-418.
ISBN978-2-87419-081-0
Publisher versionhttps://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2013-57.pdf
Files | Description | Size | Format | View |
---|---|---|---|---|
es2013-57.pdf | 616,8Kb | View/Open |