Current practices in clinical gait analysis in Europe: A comprehensive survey-based study from the European society for movement analysis in adults and children (ESMAC) standard initiative.

Clinical gait analysis Electromyography Kinematics Kinetics Standards Surveys and Questionnaires Walking

Journal

Gait & posture
ISSN: 1879-2219
Titre abrégé: Gait Posture
Pays: England
ID NLM: 9416830

Informations de publication

Date de publication:
22 Apr 2024
Historique:
received: 21 11 2023
revised: 09 04 2024
accepted: 11 04 2024
medline: 24 4 2024
pubmed: 24 4 2024
entrez: 23 4 2024
Statut: aheadofprint

Résumé

Clinical gait analysis (CGA) is a systematic approach to comprehensively evaluate gait patterns, quantify impairments, plan targeted interventions, and evaluate the impact of interventions. However, international standards for CGA are currently lacking, resulting in various national initiatives. Standards are important to ensure safe and effective healthcare practices and to enable evidence-based clinical decision-making, facilitating interoperability, and reimbursement under national healthcare policies. Collaborative clinical and research work between European countries would benefit from common standards. This study aimed to review the current laboratory practices for CGA in Europe. A comprehensive survey was conducted by the European Society for Movement Analysis in Adults and Children (ESMAC), in close collaboration with the European national societies. The survey involved 97 gait laboratories across 16 countries. The survey assessed several aspects related to CGA, including equipment used, data collection, processing, and reporting methods. There was a consensus between laboratories concerning the data collected during CGA. The Conventional Gait Model (CGM) was the most used biomechanical model for calculating kinematics and kinetics. Respondents also reported the use of video recording, 3D motion capture systems, force plates, and surface electromyography. While there was a consensus on the reporting of CGA data, variations were reported in training, documentation, data preprocessing and equipment maintenance practices. The findings of this study will serve as a foundation for the development of standardized guidelines for CGA in Europe.

Sections du résumé

BACKGROUND BACKGROUND
Clinical gait analysis (CGA) is a systematic approach to comprehensively evaluate gait patterns, quantify impairments, plan targeted interventions, and evaluate the impact of interventions. However, international standards for CGA are currently lacking, resulting in various national initiatives. Standards are important to ensure safe and effective healthcare practices and to enable evidence-based clinical decision-making, facilitating interoperability, and reimbursement under national healthcare policies. Collaborative clinical and research work between European countries would benefit from common standards.
RESEARCH OBJECTIVE OBJECTIVE
This study aimed to review the current laboratory practices for CGA in Europe.
METHODS METHODS
A comprehensive survey was conducted by the European Society for Movement Analysis in Adults and Children (ESMAC), in close collaboration with the European national societies. The survey involved 97 gait laboratories across 16 countries. The survey assessed several aspects related to CGA, including equipment used, data collection, processing, and reporting methods.
RESULTS RESULTS
There was a consensus between laboratories concerning the data collected during CGA. The Conventional Gait Model (CGM) was the most used biomechanical model for calculating kinematics and kinetics. Respondents also reported the use of video recording, 3D motion capture systems, force plates, and surface electromyography. While there was a consensus on the reporting of CGA data, variations were reported in training, documentation, data preprocessing and equipment maintenance practices.
SIGNIFICANCE CONCLUSIONS
The findings of this study will serve as a foundation for the development of standardized guidelines for CGA in Europe.

Identifiants

pubmed: 38653178
pii: S0966-6362(24)00103-6
doi: 10.1016/j.gaitpost.2024.04.014
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

65-74

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Stéphane Armand (S)

Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland. Electronic address: stephane.armand@unige.ch.

Zimi Sawacha (Z)

Department of Information Engineering, University of Padova, Padova, Italy.

Marije Goudriaan (M)

Utrecht University, University Corporate Offices, Student and Academic Affairs Office, Utrecht, the Netherlands; Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam, the Netherlands.

Brian Horsak (B)

Center for Digital Health and Social Innovation, St. Pölten University of Applied Sciences, St. Pölten, Austria.

Marjolein van der Krogt (M)

Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands.

Catherine Huenaerts (C)

Clinical Motion Analysis Laboratory, University Hospital Leuven, Leuven, Belgium.

Colm Daly (C)

National Centre for Movement Analysis, Central Remedial Clinic, Dublin, Ireland; CP-Life Research Centre, Royal College of Surgeons, Dublin, Ireland.

Andreas Kranzl (A)

Laboratory for Gait and Movement Analysis, Orthopaedic Hospital Speising, Vienna, Austria.

Harald Boehm (H)

Orthopaedic Hospital for Children, Aschau im Chiemgau, Germany.

Maurizio Petrarca (M)

Movement Analysis and Robotics Laboratory, "Bambino Gesù" Children's Hospital - IRCCS, Rome, Italy.

Anna Guiotto (A)

Department of Information Engineering, University of Padova, Padova, Italy.

Andrea Merlo (A)

Gait & Motion Analysis Laboratory, Sol et Salus Hospital, Rimini, Italy; LAM - Motion Analysis Laboratory, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, San Sebastiano Hospital, Correggio, Italy.

Fabiola Spolaor (F)

Department of Information Engineering, University of Padova, Padova, Italy.

Isabella Campanini (I)

LAM - Motion Analysis Laboratory, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, San Sebastiano Hospital, Correggio, Italy.

Michela Cosma (M)

Motion Analysis Laboratory, Neuroscience and Rehabilitation Department, University Hospital of Ferrara, Italy.

Ann Hallemans (A)

Research Group MOVANT, Department of Rehabilitation Sciences and Physiotherapy (REVAKI), University of Antwerp, Wilrijk, Belgium.

Herwin Horemans (H)

Department of Rehabilitation, Erasmus University Medical Center, Rotterdam, the Netherlands.

David Gasq (D)

Department of Functional Physiological Explorations, University Hospital of Toulouse, Hôpital de Rangueil, Toulouse, France; ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, Université Paul Sabatier, Toulouse, France.

Florent Moissenet (F)

Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.

Ayman Assi (A)

Faculty of Medicine, Saint Joseph University of Beirut, Beirut, Lebanon.

Morgan Sangeux (M)

University Children's Hospital Basel, Basel, Switzerland.

Classifications MeSH