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Computer Vision Methods for Parkinsonian Gait Analysis: A Review on Patents
Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University, Vasteras 72123, Sweden. (PAULINA)ORCID iD: 0000-0002-2752-3712
Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
2013 (English)In: Recent Patents on Biomedical Engineering, ISSN 1874-7647, Vol. 6, no 2, 97-108 p.Article in journal (Refereed) Published
Abstract [en]

Gait disturbance is an important symptom of Parkinson’s disease (PD). This paper presents a review of patents reported in the area of computerized gait disorder analysis. The feasibility of marker-less vision based systems has been examined for ‘at-home’ self-evaluation of gait taking into account the physical restrictions of patients arise due to PD. A three tier review methodology has been utilized to synthesize gait applications to investigate PD related gait features and to explore methods for gait classification based on symptom severities. A comparison between invasive and non-invasive methods for gait analysis revealed that marker-free approach can provide resource efficient, convenient and accurate gait measurements through the use of image processing methods. Image segmentation of human silhouette is the major challenge in the marker-free systems which can possibly be comprehended through the use of Microsoft Kinect application and motion estimation algorithms. Our synthesis further suggests that biorhythmic features in gait patterns have potential to discriminate gait anomalies based on the clinical scales. 

Place, publisher, year, edition, pages
Netherlands: Bentham Science Publishers , 2013. Vol. 6, no 2, 97-108 p.
Keyword [en]
Gait Impairment, Parkinson’s disease, Gait Video Analysis, and Image Processing.
National Category
Engineering and Technology
Research subject
Komplexa system - mikrodataanalys, PAULINA - Uppföljning av Parkinsonsymptom från hemmet
Identifiers
URN: urn:nbn:se:du-12731DOI: 10.2174/1874764711306020004OAI: oai:DiVA.org:du-12731DiVA: diva2:638300
Funder
Knowledge Foundation
Available from: 2013-07-29 Created: 2013-07-29 Last updated: 2015-06-29Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf