Gait Monitoring and Walk Distance Estimation With an Accelerometer During 6-Minute Walk Test.


Journal

Respiratory care
ISSN: 1943-3654
Titre abrégé: Respir Care
Pays: United States
ID NLM: 7510357

Informations de publication

Date de publication:
Aug 2019
Historique:
pubmed: 20 6 2019
medline: 1 7 2020
entrez: 20 6 2019
Statut: ppublish

Résumé

The 6-min walk test (6MWT) encompasses potential and untapped information related to exercise capacity. However, this test does not yield any information about gait pattern. Recently, we used a ventilatory polygraph to reveal respiratory adaptation during the 6MWT with subjects having high or low body mass index (BMI). In this study, we aimed to determine gait parameters with the same device, which integrates an accelerometer. Using a 30-m corridor, steps and U-turns were detected with a custom-made algorithm, compared to video recordings as a reference method, and analyzed offline. From the vertical acceleration signal, we were able to determine cadence and step length, and we could calculate the total distance covered in 6 min (6MWD). We then compared these variables between subjects with low BMI ( Steps and U-turn detection correlated with video results ( Our results demonstrated that a ventilatory polygraph with an embedded accelerometer can be used to detect steps and U-turns, and to calculate 6MWD. This method is sufficiently sensitive to characterize significant BMI-dependent differences in gait pattern during a 6MWT and appears to be a promising tool for routine clinical use.

Sections du résumé

BACKGROUND BACKGROUND
The 6-min walk test (6MWT) encompasses potential and untapped information related to exercise capacity. However, this test does not yield any information about gait pattern. Recently, we used a ventilatory polygraph to reveal respiratory adaptation during the 6MWT with subjects having high or low body mass index (BMI). In this study, we aimed to determine gait parameters with the same device, which integrates an accelerometer.
METHODS METHODS
Using a 30-m corridor, steps and U-turns were detected with a custom-made algorithm, compared to video recordings as a reference method, and analyzed offline. From the vertical acceleration signal, we were able to determine cadence and step length, and we could calculate the total distance covered in 6 min (6MWD). We then compared these variables between subjects with low BMI (
RESULTS RESULTS
Steps and U-turn detection correlated with video results (
CONCLUSION CONCLUSIONS
Our results demonstrated that a ventilatory polygraph with an embedded accelerometer can be used to detect steps and U-turns, and to calculate 6MWD. This method is sufficiently sensitive to characterize significant BMI-dependent differences in gait pattern during a 6MWT and appears to be a promising tool for routine clinical use.

Identifiants

pubmed: 31213569
pii: respcare.06144
doi: 10.4187/respcare.06144
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

923-930

Informations de copyright

Copyright © 2019 by Daedalus Enterprises.

Déclaration de conflit d'intérêts

The authors have disclosed no conflicts of interest.

Auteurs

Yann Retory (Y)

Centre EXPLOR!, Air Liquide European Homecare Operations Services, Gentilly, France.
U1179 Inserm, Laboratoire de Physiologie TITAN, Montigny-le-Bretonneux, France.
Service de Physiologie-Explorations Fonctionnelles, Hôpital Ambroise Paré, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Paris Ile-de-France Ouest, Boulogne-Billancourt, France.

Pascal David (P)

Service de Médecine Physique et Rééducation, Centre Hospitalier d'Abbeville, Abbeville, France.

Pauline Niedzialkowski (P)

Service de Physiologie-Explorations Fonctionnelles, Hôpital Ambroise Paré, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Paris Ile-de-France Ouest, Boulogne-Billancourt, France.

Carole de Picciotto (C)

Service de Physiologie-Explorations Fonctionnelles, Hôpital Ambroise Paré, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Paris Ile-de-France Ouest, Boulogne-Billancourt, France.

Marcel Bonay (M)

U1179 Inserm, Laboratoire de Physiologie TITAN, Montigny-le-Bretonneux, France.
Service de Physiologie-Explorations Fonctionnelles, Hôpital Ambroise Paré, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Paris Ile-de-France Ouest, Boulogne-Billancourt, France.

Michel Petitjean (M)

Service d'Explorations Fonctionnelles Multidisciplinaires bi-site, Hôpital Antoine Béclère, Groupe Hospitalier Paris-Sud, Clamart, France; CIAMS, Univ. Paris-Sud, Université Paris-Saclay, 91405 Orsay Cedex, France; and CIAMS, Université d'Orléans, 45067, Orléans, France. michel.petitjean134@gmail.com.

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Classifications MeSH