Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson's Disease.

Parkinson’s disease inertial sensors machine learning algorithm spatiotemporal gait parameters three-dimensional gait analysis wearables

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
18 Nov 2021
Historique:
received: 27 10 2021
revised: 15 11 2021
accepted: 16 11 2021
entrez: 27 11 2021
pubmed: 28 11 2021
medline: 1 12 2021
Statut: epublish

Résumé

Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson's Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 × 10 m walking test by reliability analysis using intra-class correlation and Bland-Altman plots. Additionally, gait parameters of an age-matched healthy control group (

Identifiants

pubmed: 34833755
pii: s21227680
doi: 10.3390/s21227680
pmc: PMC8623101
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

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Auteurs

Verena Jakob (V)

Movement and Gait Lab, Sana-Krankenhaus Rummelsberg, 90592 Schwarzenbruck, Germany.

Arne Küderle (A)

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany.

Felix Kluge (F)

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany.

Jochen Klucken (J)

Digital Medicine, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg.
Digital Medicine, Luxembourg Institute of Health, 1445 Strassen, Luxembourg.

Bjoern M Eskofier (BM)

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany.

Jürgen Winkler (J)

Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.

Martin Winterholler (M)

Department of Neurology, Sana-Krankenhaus Rummelsberg, 90592 Schwarzenbruck, Germany.

Heiko Gassner (H)

Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.
Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, 91058 Erlangen, Germany.

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