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Remote Monitoring in the Home Validates Clinical Gait Measures for Multiple Sclerosis

Authors :
Akara Supratak
Gourab Datta
Arie R. Gafson
Richard Nicholas
Yike Guo
Paul M. Matthews
Source :
Frontiers in Neurology, Vol 9 (2018)
Publication Year :
2018
Publisher :
Frontiers Media S.A., 2018.

Abstract

Background: The timed 25-foot walk (T25FW) is widely used as a clinic performance measure, but has yet to be directly validated against gait speed in the home environment.Objectives: To develop an accurate method for remote assessment of walking speed and to test how predictive the clinic T25FW is for real-life walking.Methods: An AX3-Axivity tri-axial accelerometer was positioned on 32 MS patients (Expanded Disability Status Scale [EDSS] 0–6) in the clinic, who subsequently wore it at home for up to 7 days. Gait speed was calculated from these data using both a model developed with healthy volunteers and individually personalized models generated from a machine learning algorithm.Results: The healthy volunteer model predicted gait speed poorly for more disabled people with MS. However, the accuracy of individually personalized models was high regardless of disability (R-value = 0.98, p-value = 1.85 × 10−22). With the latter, we confirmed that the clinic T25FW is strongly predictive of the maximum sustained gait speed in the home environment (R-value = 0.89, p-value = 4.34 × 10−8).Conclusion: Remote gait monitoring with individually personalized models is accurate for patients with MS. Using these models, we have directly validated the clinical meaningfulness (i.e., predictiveness) of the clinic T25FW for the first time.

Details

Language :
English
ISSN :
16642295
Volume :
9
Database :
Directory of Open Access Journals
Journal :
Frontiers in Neurology
Publication Type :
Academic Journal
Accession number :
edsdoj.974426ee3daf4d6396845fedb8ac90ed
Document Type :
article
Full Text :
https://doi.org/10.3389/fneur.2018.00561