Journal article
Accuracy, reliability, and validity of a spatiotemporal gait analysis system
Medical engineering & physics, v 28(5), pp 460-467
01 Jun 2006
PMID: 16122966
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Making evidence-based decisions in the clinical management of gait dysfunction requires the ability to measure spatiotemporal gait variables validly and reliably. This study examined the accuracy, reliability, and validity of a clinical gait analysis system that is relatively inexpensive and portable, the GaitMat II (GM).
The trustworthiness of measures taken with the GM was investigated by comparing the placement of the switches on three different GM systems. Measures taken with the GM system were compared with the same measures taken simultaneously with the Vicon motion analysis system, using a repetitive dynamic signal presented to both systems.
Variability was present in the placement of switches on the surfaces of different GM systems. The variability in switch placement was much less than the normal variability of most gait variables measured with the GM. Excellent agreement was found between the GM and Vicon systems for timing variables but poor agreement was found for distance variables. The mean difference between the GM and Vicon measures for distance variables would have little clinical significance in adults for distance measures such as step length or stride length.
The results of these studies support the reliability and validity of the GaitMat II as a clinical gait analysis tool.
Metrics
Details
- Title
- Accuracy, reliability, and validity of a spatiotemporal gait analysis system
- Creators
- Susan Barker - Misericordia UniversityRebecca Craik - Misericordia UniversityWilliam Freedman - Misericordia UniversityNira Herrmann - Misericordia UniversityHoward Hillstrom - Misericordia University
- Publication Details
- Medical engineering & physics, v 28(5), pp 460-467
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science (Computing); [Retired Faculty]; College of Engineering
- Web of Science ID
- WOS:000238294000008
- Scopus ID
- 2-s2.0-33745329548
- Other Identifier
- 991021889913504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Biomedical