Gait Analyses of Parkinson’s Disease Patients Using Multiscale Entropy

Parkinson’s disease (PD) is a type of neurodegenerative diseases. PD influences gait in many aspects: reduced speed and step length, increased axial rigidity, impaired rhythmicity. Gait-related data used this study are from PhysioNet. Twenty-one patients five healthy controls (CO) were sorted into four groups: without task (PDw), with dual (PDd), control (COw), (COd). Since actions attention demanding, either or cognitive function may be affected. To quantify the walking data, eight pressure sensors installed each insole to measure vertical ground reaction force. Thus, quantitative measurement analysis performed utilizing multiscale entropy (MSE) complexity index (CI) analyze differentiate between force different groups. Results show that CI higher than CO 11 sensor signals statistically significant (p < 0.05). The COd group has larger values at beginning = 0.021) but they get lower end test 0.000) compared COw group. end-of-test for PDw one feet signals, right total PDd counterparts. In conclusion, when people start adjust their due pathology stress, increase first reach peak, it decreases afterward stress further increased.