Literature DB >> 33302221

Does gait bout definition influence the ability to discriminate gait quality between people with and without multiple sclerosis during daily life?

Vrutangkumar V Shah1, James McNames2, Graham Harker3, Carolin Curtze4, Patricia Carlson-Kuhta3, Rebecca I Spain5, Mahmoud El-Gohary6, Martina Mancini3, Fay B Horak7.   

Abstract

BACKGROUND: There is currently no consensus about standardized gait bout definitions when passively monitoring walking during normal daily life activities. It is also not known how different definitions of a gait bout in daily life monitoring affects the ability to distinguish pathological gait quality. Specifically, how many seconds of a pause with no walking indicates an end to one gait bout and the start of another bout? In this study, we investigated the effect of 3 gait bout definitions on the discriminative ability to distinguish quality of walking in people with multiple sclerosis (MS) from healthy control subjects (HC) during a week of daily living.
METHODS: 15 subjects with MS and 16 HC wore instrumented socks on each foot and one Opal sensor over the lower lumbar area for a week of daily activities for at least 8 h/day. Three gait bout definitions were based on the length of the pause between the end of one gait bout and start of another bout (1.25 s, 2.50 s, and 5.0 s pause). Area under the curve (AUC) was used to compare gait quality measures in MS versus HC.
RESULTS: Total number of gait bouts over the week were statistically significantly different across bout definitions, as expected. However, AUCs of gait quality measures (such as gait speed, stride length, stride time) discriminating people with MS from HC were not different despite the 3 bout definitions. SIGNIFICANCE: Quality of gait measures that discriminate MS from HC during daily life are not influenced by the length of a gait bout, despite large differences in quantity of gait across bout definitions. Thus, gait quality measures in people with MS versus controls can be compared across studies using different gait bout definitions with pause lengths ≤5 s.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bout; Free-living; Gait; Multiple sclerosis; Wearable sensors

Mesh:

Year:  2020        PMID: 33302221      PMCID: PMC7946343          DOI: 10.1016/j.gaitpost.2020.11.024

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  36 in total

1.  Gait variability in multiple sclerosis: a better falls predictor than EDSS in patients with low disability.

Authors:  Gilles Allali; Magali Laidet; Francois R Herrmann; Stéphane Armand; Charlotte Elsworth-Edelsten; Frédéric Assal; Patrice H Lalive
Journal:  J Neural Transm (Vienna)       Date:  2016-02-04       Impact factor: 3.575

2.  Does the evaluation of gait quality during daily life provide insight into fall risk? A novel approach using 3-day accelerometer recordings.

Authors:  Aner Weiss; Marina Brozgol; Moran Dorfman; Talia Herman; Shirley Shema; Nir Giladi; Jeffrey M Hausdorff
Journal:  Neurorehabil Neural Repair       Date:  2013-06-17       Impact factor: 3.919

3.  Mobility Lab to Assess Balance and Gait with Synchronized Body-worn Sensors.

Authors:  Martina Mancini; Laurie King; Arash Salarian; Lars Holmstrom; James McNames; Fay B Horak
Journal:  J Bioeng Biomed Sci       Date:  2011-12-12

Review 4.  Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria.

Authors:  Alan J Thompson; Brenda L Banwell; Frederik Barkhof; William M Carroll; Timothy Coetzee; Giancarlo Comi; Jorge Correale; Franz Fazekas; Massimo Filippi; Mark S Freedman; Kazuo Fujihara; Steven L Galetta; Hans Peter Hartung; Ludwig Kappos; Fred D Lublin; Ruth Ann Marrie; Aaron E Miller; David H Miller; Xavier Montalban; Ellen M Mowry; Per Soelberg Sorensen; Mar Tintoré; Anthony L Traboulsee; Maria Trojano; Bernard M J Uitdehaag; Sandra Vukusic; Emmanuelle Waubant; Brian G Weinshenker; Stephen C Reingold; Jeffrey A Cohen
Journal:  Lancet Neurol       Date:  2017-12-21       Impact factor: 44.182

Review 5.  A roadmap for implementation of patient-centered digital outcome measures in Parkinson's disease obtained using mobile health technologies.

Authors:  Alberto J Espay; Jeffrey M Hausdorff; Álvaro Sánchez-Ferro; Jochen Klucken; Aristide Merola; Paolo Bonato; Serene S Paul; Fay B Horak; Joaquin A Vizcarra; Tiago A Mestre; Ralf Reilmann; Alice Nieuwboer; E Ray Dorsey; Lynn Rochester; Bastiaan R Bloem; Walter Maetzler
Journal:  Mov Disord       Date:  2019-03-22       Impact factor: 10.338

Review 6.  Free-living monitoring of Parkinson's disease: Lessons from the field.

Authors:  Silvia Del Din; Alan Godfrey; Claudia Mazzà; Sue Lord; Lynn Rochester
Journal:  Mov Disord       Date:  2016-07-25       Impact factor: 10.338

Review 7.  Wearable biosensors to monitor disability in multiple sclerosis.

Authors:  Michael J Bradshaw; Samantha Farrow; Robert W Motl; Tanuja Chitnis
Journal:  Neurol Clin Pract       Date:  2017-08

Review 8.  Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review.

Authors:  Valerie A J Block; Erica Pitsch; Peggy Tahir; Bruce A C Cree; Diane D Allen; Jeffrey M Gelfand
Journal:  PLoS One       Date:  2016-04-28       Impact factor: 3.240

9.  Is every-day walking in older adults more analogous to dual-task walking or to usual walking? Elucidating the gaps between gait performance in the lab and during 24/7 monitoring.

Authors:  Inbar Hillel; Eran Gazit; Alice Nieuwboer; Laura Avanzino; Lynn Rochester; Andrea Cereatti; Ugo Della Croce; Marcel Olde Rikkert; Bastiaan R Bloem; Elisa Pelosin; Silvia Del Din; Pieter Ginis; Nir Giladi; Anat Mirelman; Jeffrey M Hausdorff
Journal:  Eur Rev Aging Phys Act       Date:  2019-05-03       Impact factor: 3.878

10.  Laboratory versus daily life gait characteristics in patients with multiple sclerosis, Parkinson's disease, and matched controls.

Authors:  Vrutangkumar V Shah; James McNames; Martina Mancini; Patricia Carlson-Kuhta; Rebecca I Spain; John G Nutt; Mahmoud El-Gohary; Carolin Curtze; Fay B Horak
Journal:  J Neuroeng Rehabil       Date:  2020-12-01       Impact factor: 4.262

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  1 in total

1.  Fall Prediction Based on Instrumented Measures of Gait and Turning in Daily Life in People with Multiple Sclerosis.

Authors:  Ishu Arpan; Vrutangkumar V Shah; James McNames; Graham Harker; Patricia Carlson-Kuhta; Rebecca Spain; Mahmoud El-Gohary; Martina Mancini; Fay B Horak
Journal:  Sensors (Basel)       Date:  2022-08-09       Impact factor: 3.847

  1 in total

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