Validation of Estimators for Weight-Bearing and Shoulder Joint Loads Using Instrumented Crutches.

biomechanical model gait analysis instrumented crutches load measurement partial weight-bearing shoulder joint shoulder load walking aid

Journal

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

Informations de publication

Date de publication:
07 Jul 2023
Historique:
received: 06 06 2023
revised: 05 07 2023
accepted: 05 07 2023
medline: 17 7 2023
pubmed: 14 7 2023
entrez: 14 7 2023
Statut: epublish

Résumé

This research paper aimed to validate two methods for measuring loads during walking with instrumented crutches: one method to estimate partial weight-bearing on the lower limbs and another to estimate shoulder joint reactions. Currently, gait laboratories, instrumented with high-end measurement systems, are used to extract kinematic and kinetic data, but such facilities are expensive and not accessible to all patients. The proposed method uses instrumented crutches to measure ground reaction forces and does not require any motion capture devices or force platforms. The load on the lower limbs is estimated by subtracting the forces measured by the crutches from the subject's total weight. Since the model does not consider inertia contribution in dynamic conditions, the estimation improves with low walking cadence when walking with the two-point contralateral and the three-point partial weight-bearing patterns considered for the validation tests. The shoulder joint reactions are estimated using linear regression, providing accurate values for the forces but less accurate torque estimates. The crutches data are acquired and processed in real-time, allowing for immediate feedback, and the system can be used outdoors in real-world walking conditions. The validation of this method could lead to better monitoring of partial weight-bearing and shoulder joint reactions, which could improve patient outcomes and reduce complications.

Identifiants

pubmed: 37448059
pii: s23136213
doi: 10.3390/s23136213
pmc: PMC10347278
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : European Union
ID : 779963

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Auteurs

Marco Ghidelli (M)

Department of Information Engineering, Università degli Studi di Brescia, 25123 Brescia, Italy.

Cristina Nuzzi (C)

Department of Mechanical and Industrial Engineering, Università degli Studi di Brescia, 25123 Brescia, Italy.

Francesco Crenna (F)

Department of Mechanical, Energy, Management and Transport Engineering, Università degli Studi di Genova, 16145 Genova, Italy.

Matteo Lancini (M)

Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, Università degli Studi di Brescia, 25121 Brescia, Italy.

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Classifications MeSH