Graphical-based multivariate analysis for knee joint clinical and kinematic data correlation assessment

Fatima Bensalma, Glen Richardson, Youssef Ouakrim, Alexandre Fuentes, Michael Dunbar, Nicola Hagemeister, Neila Mezghani

Producción científica: Capítulo en Libro/Reporte/Acta de conferenciaContribución a la conferencia

2 Citas (Scopus)

Resumen

A large amount of data including joint kinematics, joint kinetics, clinical and functional measurements constitutes the clinical gait analysis basis which is a process whereby quantitative gait information are collected to aid in clinical decision-making. Therefore, better understanding the relationship between the biomechanical and clinical data for the knee osteoarthritis (OA) patient is for a relevant importance. It's the purpose of this paper, which aims to analyze and visualize the correlation structure between biomechanical characteristics and clinical symptoms, and thus to provide an additional knowledge from the coupling of these parameters that will be useful for the pathology assessment of knee-joint disease in the end-staged knee OA patients. We perform two multivariate statistical approaches, first, a Canonical Correlation Analysis (CCA) to assess the multivariate association and, second, a graphical- based representation of the multivariate correlation to better understand the association between these multivariate data. Results show the usefulness of using such multivariate approaches to highlight association and specific correlation structure between the features and to extract meaningful information.

Idioma originalEnglish
Título de la publicación alojada42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtítulo de la publicación alojadaEnabling Innovative Technologies for Global Healthcare, EMBC 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas5362-5368
Número de páginas7
ISBN (versión digital)9781728119908
DOI
EstadoPublished - jul. 2020
Publicado de forma externa
Evento42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duración: jul. 20 2020jul. 24 2020

Serie de la publicación

NombreProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volumen2020-July
ISSN (versión impresa)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
País/TerritorioCanada
CiudadMontreal
Período7/20/207/24/20

Nota bibliográfica

Publisher Copyright:
© 2020 IEEE.

ASJC Scopus Subject Areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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