Entropy measures in dynamical systems and their viability in characterizing bipedal walking gait dynamics

dc.contributor.authorLeverick, Graham
dc.contributor.examiningcommitteeTelichev, Igor (Mechanical Engineering) Gumel, Abba (Mathematics)en_US
dc.contributor.supervisorWu, Christine (Mechanical Engineering) Szturm, Tony (Medical Rehabilitation)en_US
dc.date.accessioned2013-09-11T17:47:54Z
dc.date.available2013-09-11T17:47:54Z
dc.date.issued2013-09-11
dc.degree.disciplineMechanical and Manufacturing Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractEntropy measures have been widely used to quantify the complexity of theoretical and experimental dynamical systems. In this thesis, two novel entropy measures are developed based on using coarse quantization to classify and compare dynamical features within a time series; quantized dynamical entropy (QDE) and a quantized approximation of sample entropy (QASE). Following this, comprehensive guidelines for the quantification of complexity are presented based on a detailed investigation of the performance characteristics of the two developed measures and three existing measures; permutation entropy, sample entropy and fuzzy entropy. The sensitivity of the considered entropy measures to changes in dynamics was assessed using the case study of characterizing bipedal walking gait dynamics. Based on the analysis conducted, it was found that sample entropy and fuzzy entropy, while computationally inefficient, provide the best overall performance. In instances where computational efficiency is vital, QDE and QASE serve as viable alternatives to existing methods.en_US
dc.description.noteOctober 2013en_US
dc.identifier.urihttp://hdl.handle.net/1993/22172
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectDynamical systemsen_US
dc.subjectEntropyen_US
dc.subjectComplexityen_US
dc.subjectTime seriesen_US
dc.titleEntropy measures in dynamical systems and their viability in characterizing bipedal walking gait dynamicsen_US
dc.typemaster thesisen_US
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