title: Modeling the gait of normal and Parkinsonian persons for improving the diagnosis.
abstract: In this study, we present a model for the gait of normal and Parkinson's disease (PD) persons. Gait is semi-periodic and has fractal properties. Sine circle map (SCM) relation has a sinusoidal term and can show chaotic behaviour. Therefore, we used SCM as a basis for our model structure. Moreover, some similarities exist between the parameters of this relation and basal ganglia (BG) structure. This relation can explain the complex behaviours and the complex structure of BG. The presented model can simulate the BG behaviour globally. A model parameter, Ω, has a key role in the model response. We showed that when Ω is between 0.6 and 0.8, the model simulates the behaviour of normal persons; the amounts greater or less than this range correspond to PD persons. Our statistical tests show that there is a significant difference between the Ω of normal and PD patients. We conclude that Ω can be introduced as a parameter to distinguish normal and PD persons. Additionally, our results showed that Spearman correlation between the Ω and the severity of PD is 0.586. This parameter may be a good index of PD severity.
authors.affiliation: Neuromuscular Systems Laboratory, Biomedical Engineering Faculty, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
authors.forename: Yashar
authors.initials: Y
authors.lastname: Sarbaz
authors.forename: Masood
authors.initials: M
authors.lastname: Banaie
authors.forename: Mohammad
authors.initials: M
authors.lastname: Pooyan
authors.forename: Shahriar
authors.initials: S
authors.lastname: Gharibzadeh
authors.forename: Farzad
authors.initials: F
authors.lastname: Towhidkhah
authors.forename: Ayyoob
authors.initials: A
authors.lastname: Jafari
mesh_terms: D000704:Analysis of Variance; D016022:Case-Control Studies; D017709:Fractals; D005684:Gait / Q000502:physiology*; D006262:Health; D006801:Humans; D008954:Models, Biological; D010300:Parkinson Disease / Q000175:diagnosis* / Q000503:physiopathology*; D015203:Reproducibility of Results