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TitleFeature reduction and multi-classification of different assistive devices according to the gait pattern
Author(s)Martins, Maria
Santos, Cristina
Costa, Lino
Frizera, Anselmo
KeywordsAssistive devices
Feature reduction
Gait analysis
Genetic algorithms
Multi-class classification
Issue date2016
PublisherTaylor and Francis
JournalDisability and Rehabilitation-Assistive Technology
Abstract(s)Total knee arthroplasty (TKA) is a surgical procedure used in patients with Osteoarthritis to improve their state. An understanding about how gait patterns differ from patient to patient and are influenced by the assistive device (AD) that is prescribed is still missing. This article focuses on such purpose. Standard walker, crutches and rollator were tested. Symmetric indexes of spatiotemporal and postural control features were calculated. In order to select the important features which can discriminate the differences among the ADs, different techniques for feature selection are investigated. Classification is handled by Multi-class Support Vector Machine. Results showed that rollator provides a more symmetrical gait and crutches demonstrated to be the worst. Relatively to postural control parameters, standard walker is the most stable and crutches are the worst AD. This means that, depending on the patient's problem and the recovery goal, different ADs should be used. After selecting a set of 16 important features, through correlation, it was demonstrated that they provide important quantitative information about the functional capacity, which is not represented by velocity, cadence and clinical scales. Also, they were capable of distinguishing the gait patterns influenced by each AD, showing that each patient has different needs during recovery.
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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