Quantification Of Gait Disorder In Parkinson's Disease Using The Three Dimensional Force Platform

BackgroundParkinson's disease( PD) with high prevalence rate, high disability rate characteristics and the complex forms of movement disorders, seriously impacts on public health and quality of life. Neurologists rely on clinical experience and application of UPDRS scale to assess the dyskinesias of PD. At present, however, the difference between the clinical experience of neurologists, often leads to the accuracy and stability of the evaluation being not ideal, and resulting in misdiagnosis and mistreatment. It becomes severely affecting patients condition and prognosis. In addition, the dyskinesia symptoms are crossing and overlapping between PD and other types of Parkinsonian syndromes(PS), especially in the early period. But, it is lack to identify the specific indicators between PD and other types of PS.With the incessant development of biomechanical information acquisition technology and analysis methods, domestic and foreign scholars studied dyskinesia in PD patients being related biomechanical information acquisition, processing and feature extraction in terms of researchs.Our group in the previous study, respectively, use the flexible pressure inertial sensor to collect PD walking gait parameters and use finger inertial sensor to collect PD fingers resting and postural tremor. The results commendably show PD dyskinesia of objective and quantitative data, and further to extract some characteristic parameters for the identification of PD and other types of PS.This paper on the basis of previous research, uses the three-dimensional dynamometer to measure the gait dynamics data of PD, quantitative assessment the gait disorder severity, and to look for further characteristic meaningful indicators between PD and other types of PS, to provide help for the clinical diagnosis and differentialdiagnosis.Objective1. Gait dynamic data acquisition of PD patients is carried out by using the three dimensional force platform, and the severity of gait disturbance is assessed quantitatively, which provided objective basis for gait disturbance symptoms and curative effect evaluation.2. Analysis for the parameters identification of significant differences between PD and other types of PS can be used to provide help for the clinical diagnosis and differential diagnosis.Method1. According to the diagnostic criteria of PD and PS, the cases were divided into Parkinson's disease group(PD group) and other types of Parkinson syndrome group(PS group), and the normal control group(NC group) with the same age as physical examination.2. Using the UPDRS Part III about gait score for the clinical rating of PD and PS groups' gait. The three-dimensional dynamometer is used to detect the PD group and PS group and NC group of gait, and the gait analysis software to calculate the related parameters(including walking time(T), the three-dimensional orientation(Fx, Fy and Fz) shear stress(normalization) extremum(maximum value Max and minimum value min), DFA, RPDE).3. Using statistical software SPSS17.0 to analyze the data. The mean value of the measurement data is represented by the standard deviation( sx ±), and the measurement data are compared between the two groups. The normal test and the t test are used. Among the three groups that meet the homogeneity of variance,one-way analysis of variance is used, among which pairwise comparison by SNK test.Using correlation analysis to study the relationship between variables. ?=0.05 for the significance test standard, P<0.05 for a significant statistical significance, P<0.01 for a very significant statistical significance, P>0.05 for no significant statistical significance.Result1. PD group and PS group walking time obviously prolonged T compared to NC group(P<0.01), while there's no significant difference about walking time T between the PD group and PS group(P>0.05).2. PD group and PS group Fxmax/m, Fxmin/m are significantly higher than the NC group(P<0.01), while there's no significant difference about Fxmax/m, Fxmin/m between the PD group and PS group(P>0.05)3. PD group and PS group Fymax/m Fymin/m are significantly decreased compared with NC group(P<0.01), PD group Fymax/m is decreased compared with PS group(P<0.05), and there is no significant difference about Fymin/m between PD group and PS group(P>0.05).4. PD group and PS group Fzmax/m, Fzmin/m are significantly higher than the NC group(P<0.01), while there's no significant difference about Fxmax/m, Fxmin/m between the PD group and PS group(P>0.05).5. PD group and PS group full scale index ? and short scale index of ?1 are significantly decreased compared with NC group(P<0.01), the PD group ? is significantly decreased compared with the PS group(P<0.01), while the PD group and the PS group is no significant difference between the ?1(P>0.05). PD group and PS group ?2 are significantly increased compared with NC group(P<0.01), while there's no significant difference about ?2 between the PD group and PS group(P>0.05)6. PD group and PS group RPDE are significantly increased compared with NC group(P<0.01), while there's no significant difference about RPDE between the PD group and PS group(P>0.05)7. PD quantitative classification research results:(1) The course of disease, H-Y classification and UPDRS score have higher positive correlation, and the correlation coefficient is more than 0.7.(2) T, Fxmax/m, Fxmin/m, Fymax/m, Fzmin/m in the PD level are significant statistical differences between.(3) T, Fxmax/m, Fxmin/m, Fymax/m, RPDE parameters compaerd with UPDRS scale gait score has a higher correlation, correlation coefficient is greater than 0.7.Conclusion1. It can realize to get the real-time precise quantitative PD plantar pressure by using the three dimensional force platform.2. The related parameters extracted by the three dimensional force platform has good correlation compared with UPDRS scale gait score, which can be used as PD gait disorder severity of graded index of reference.