Skip navigation
 

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/13092
Title: Classification Algorithm: Application to Orthotic  Bracing
???metadata.dc.contributor.*???: DEmoze G. (PhD)
Tewedage, Sileshi
Keywords: Gait classification;Feature extraction;Inertial motion sensor;Machine learning;Orthotic bracing;Performance analysis;Confusion matrix;hold out cross valdation
Issue Date: Oct-2016
Publisher: AAU
Abstract: Orthotic bracing are fitted to improve the quality of a deviating gait cycle, nevertheless recent studies show that gait cycle deviations are seen due to bracing [4, 36]. In order to correct the deviation, adjustments should be made in all stages of the process to which it requires evaluating the deviation. So the objective of this paper is to develop and analyze the performance of an algorithm for gait classification, to assess the deviation of gait cycle due to Orthotic bracing. Acceleration data was taken as an input from Inertial Motion Sensor attached at the foot of a healthy subject. The algorithm was developed using Model based approach, by considering four machine learning classifiers. The performance of the algorithm was analyzed using the performance indicators. The performance analysis illustrates that using categorical class type gives a relatively higher accuracy with a maximum accuracy of 86%. The performance related to the classifier on the other hand illustrates that Tree Bagger Classifier and Support Vector Machine classifier provide a higher accuracy with a balanced true rate. The analysis further indicate that the gait cycle of the braced side of an Ankle bracing is relatively expressed using the extracted features, it was expressed on average 58%. While the effect of the bracing on the unbraced side of the leg are shown more with Knee bracing.
URI: http://hdl.handle.net/123456789/13092
Appears in Collections:Thesis - Mechanical Design Engineering

Files in This Item:
File Description SizeFormat 
Tewedage Sileshi.pdf5.17 MBAdobe PDFView/Open
Show full item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.