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Assessment of waveform similarity in clinical gait data: the linear fit method

Iosa, Marco and Cereatti, Andrea and Merlo, Andrea and Campanini, Isabella and Paolucci, Stefania and Cappozzo, Aurelio (2014) Assessment of waveform similarity in clinical gait data: the linear fit method. BioMed Research International, Vol. 2014 , Article 214156. ISSN 2314-6133. eISSN 2314-6141. Article.

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DOI: 10.1155/2014/214156

Abstract

The assessment of waveform similarity is a crucial issue in gait analysis for the comparison of kinematic or kinetic patterns with reference data. A typical scenario is in fact the comparison of a patient’s gait pattern with a relevant physiological pattern. This study aims to propose and validate a simple method for the assessment of waveform similarity in terms of shape, amplitude, and offset. The method relies on the interpretation of these three parameters, obtained through a linear fit applied to the two data sets under comparison plotted one against the other after time normalization. The validity of this linear fit method was tested in terms of appropriateness (comparing real gait data of 34 patients with cerebrovascular accident with those of 15 healthy subjects), reliability, sensitivity, and specificity (applying a cluster analysis on the real data). Results showed for this method good appropriateness, 94.1% of sensitivity, 93.3% of specificity, and good reliability. The LFM resulted in a simple method suitable for analysing the waveform similarity in clinical gait analysis.

Item Type:Article
ID Code:10841
Status:Published
Refereed:Yes
Uncontrolled Keywords:Assessment of waveform similarity, gait analysis, Linear Fit Method (LFM)
Subjects:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/06 Bioingegneria elettronica e informatica
Divisions:001 Università di Sassari > 01-a Nuovi Dipartimenti dal 2012 > Scienze Politiche, Scienze della Comunicazione e Ingegneria dell'Informazione
Publisher:Hindawi Publishing Corporation
ISSN:2314-6133
eISSN:2314-6141
Copyright Holders:© 2014 M. Iosa et al.
Deposited On:17 Mar 2015 10:10

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