Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
Motion Cues Analysis for Parkinson Gait Recognition
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-2752-3712
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-0403-338X
2011 (English)In: 15th International Congress of Parkinson's Disease and Movement Disorders, Toronto, Canada, 2011Conference paper, Published paper (Refereed)
Abstract [en]

Background: Previous assessment methods for PG recognition used sensor mechanisms for PG that may cause discomfort. In order to avoid stress of applying wearable sensors, computer vision (CV) based diagnostic systems for PG recognition have been proposed. Main constraints in these methods are the laboratory setup procedures: Novel colored dresses for the patients were specifically designed to segment the test body from a specific colored background. Objective: To develop an image processing tool for home-assessment of Parkinson Gait(PG) by analyzing motion cues extracted during the gait cycles. Methods: The system is based on the idea that a normal body attains equilibrium during the gait by aligning the body posture with the axis of gravity. Due to the rigidity in muscular tone, persons with PD fail to align their bodies with the axis of gravity. The leaned posture of PD patients appears to fall forward. Whereas a normal posture exhibits a constant erect posture throughout the gait. Patients with PD walk with shortened stride angle (less than 15 degrees on average) with high variability in the stride frequency. Whereas a normal gait exhibits a constant stride frequency with an average stride angle of 45 degrees. In order to analyze PG, levodopa-responsive patients and normal controls were videotaped with several gait cycles. First, the test body is segmented in each frame of the gait video based on the pixel contrast from the background to form a silhouette. Next, the center of gravity of this silhouette is calculated. This silhouette is further skeletonized from the video frames to extract the motion cues. Two motion cues were stride frequency based on the cyclic leg motion and the lean frequency based on the angle between the leaned torso tangent and the axis of gravity. The differences in the peaks in stride and lean frequencies between PG and normal gait are calculated using Cosine Similarity measurements. Results: High cosine dissimilarity was observed in the stride and lean frequencies between PG and normal gait. High variations are found in the stride intervals of PG whereas constant stride intervals are found in the normal gait. Conclusions: We propose an algorithm as a source to eliminate laboratory constraints and discomfort during PG analysis. Installing this tool in a home computer with a webcam allows assessment of gait in the home environment.

Place, publisher, year, edition, pages
Toronto, Canada, 2011.
National Category
Computer and Information Science
Research subject
Komplexa system - mikrodataanalys, E-MOTIONS, Beslutsstöd för Parkinsonbehandling
Identifiers
URN: urn:nbn:se:du-5934ISI: 000291359502287OAI: oai:dalea.du.se:5934DiVA: diva2:522417
Conference
15th International Congress of Parkinson's Disease and Movement Disorders , Toronto, Canada, 5-9 juni, 2011
Available from: 2011-09-12 Created: 2011-09-12 Last updated: 2015-06-29Bibliographically approved

Open Access in DiVA

Paper(900 kB)83 downloads
File information
File name FULLTEXT02.pdfFile size 900 kBChecksum SHA-512
4d17e94fb537aeb82ae0a0341c90ed5562e80cf2b2c64c68e852b3f75eae004226f6e71f5e481efe43b1729ce8de469c2e55f974c3ee9dc42d623ed1ffc04b14
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Khan, TahaWestin, Jerker
By organisation
Computer Engineering
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 231 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 800 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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