Parkinsonian gait patterns quantification from principal geodesic analysis
Author:
Funder
Universidad Industrial de Santander
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition
Link
https://link.springer.com/content/pdf/10.1007/s10044-022-01115-x.pdf
Reference28 articles.
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2. Davis RB, Õunpuu S, Tyburski D, Gage JR (1991) A gait analysis data collection and reduction technique. Hum Mov Sci 10(5):575–587. https://doi.org/10.1016/0167-9457(91)90046-Z
3. Fletcher PT, Joshi S (2007) Riemannian geometry for the statistical analysis of diffusion tensor data. Natl Alliance Med Image Comput: NAMIC 87(2):250–262. https://doi.org/10.1016/j.sigpro.2005.12.018
4. Fréchet M (1948) Les éléments alatoires de nature quelconque dans un espace distanci. Annales de l’institut Henri Poincaré 10(4):215–310
5. Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez-Martin P, Poewe W, Sampaio C, Stern MB, Dodel R et al (2008) Movement disorder society-sponsored revision of the unified Parkinson’s disease rating scale (mds-updrs): scale presentation and clinimetric testing results. Mov Disord 23(15):2129–2170. https://doi.org/10.1002/mds.22340
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