Weight-Bearing Estimation for Cane Users by Using Onboard Sensors.


Journal

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

Informations de publication

Date de publication:
26 Jan 2019
Historique:
received: 05 12 2018
revised: 14 01 2019
accepted: 22 01 2019
entrez: 30 1 2019
pubmed: 30 1 2019
medline: 13 2 2019
Statut: epublish

Résumé

Mobility is a fundamental requirement for a healthy, active lifestyle. Gait analysis is widely acknowledged as a clinically useful tool for identifying problems with mobility, as identifying abnormalities within the gait profile is essential to correct them via training, drugs, or surgical intervention. However, continuous gait analysis is difficult to achieve due to technical limitations, namely the need for specific hardware and constraints on time and test environment to acquire reliable data. Wearables may provide a solution if users carry them most of the time they are walking. We propose to add sensors to walking canes to assess user's mobility. Canes are frequently used by people who cannot completely support their own weight due to pain or balance issues. Furthermore, in absence of neurological disorders, the load on the cane is correlated with the user condition. Sensorized canes already exist, but often rely on expensive sensors and major device modifications are required. Thus, the number of potential users is severely limited. In this work, we propose an affordable module for load monitoring so that it can be widely used as a screening tool. The main advantages of our module are: (i) it can be deployed in any standard cane with minimal changes that do not affect ergonomics; (ii) it can be used every day, anywhere for long-term monitoring. We have validated our prototype with 10 different elderly volunteers that required a cane to walk, either for balance or partial weight bearing. Volunteers were asked to complete a 10 m test and, then, to move freely for an extra minute. The load peaks on the cane, corresponding to maximum support instants during the gait cycle, were measured while they moved. For validation, we calculated their gait speed using a chronometer during the 10 m test, as it is reportedly related to their condition. The correlation between speed (condition) and load results proves that our module provides meaningful information for screening. In conclusion, our module monitors support in a continuous, unsupervised, nonintrusive way during users' daily routines, plus only mechanical adjustment (cane height) is needed to change from one user to another.

Identifiants

pubmed: 30691145
pii: s19030509
doi: 10.3390/s19030509
pmc: PMC6387159
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Joaquin Ballesteros (J)

Division of Intelligent Future Technologies, Mälardalen University, 721 23 Västerås, Sweden. joaquin.ballesteros@mdh.se.

Alberto Tudela (A)

Department of Electronic Technology, University of Malaga, 29071 Malaga, Spain. ajtudela@uma.es.

Juan Rafael Caro-Romero (JR)

Department of Electronic Technology, University of Malaga, 29071 Malaga, Spain. jrcaro@uma.es.

Cristina Urdiales (C)

Department of Electronic Technology, University of Malaga, 29071 Malaga, Spain. acurdiales@uma.es.

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Classifications MeSH