Gait Analysis of Patients with Parkinson’s Disease in Relation to Apposite Data Selection
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| Year of publication | 2019 |
| Type | Appeared in Conference without Proceedings |
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| Description | Introduction In Parkinson’s disease (PD) patients, the motor symptoms (tremor, freezing of gait) fall within the ones with the most deteriorating impact on quality of life. In order to introduce our unique intervention programme based on exercise with vibration rings, we must clarify what motion variables are apt to be followed and evaluated. This pilot study aims to determine the most fitting variables for the long-term observation of the motor development influenced by the intervention programme. Methods We examined 11 individuals (4 females, 7 males, 63.76 ± 10.33 yrs) diagnosed with PD. We performed 3D kinematic gait analysis (5 trials × 7 m) using the SIMI Motion system. For each individual, 15 anatomical points of the body were marked and, subsequently, 105 spatio-temporal characteristics of locomotion were evaluated. Variability and correlation between the variables were evaluated, as well as the degree of lateral asymmetry. Factor analysis was used for variables number reduction. Results The most suitable variables for assessing the developing effect of the intervention programme are the single and double support time and other gait time variables. The variability of the gait model can be determined by 71 %; the greatest significance is distributed between three factors: F1 – gait time parameters, F2 – lower limbs segments angles in initial and terminal contact with the ground, and F3 – gait velocity parameters and step dimensions. Discussion & Conclusion For the upcoming research, the time variables are the most suitable thanks to their optimal variability. The factor analysis enables fusion of analysed variables; the low level of side asymmetry in key variables authorises us to omit its influence on the gait model in PD patients. The balance abilities of the patients need to be questioned and measured in the upcoming research, for further interpretation of the data. |
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