Statistical analysis of parkinson disease gait classification using Artificial Neural Network

Abstract

The aim of this study is to investigate the parameters that could be used to identify abnormal gait pattern in Parkinson's disease subjects during normal walking. Hence, three types of gait parameters namely basic, kinematic and kinetic are evaluated. Initial findings showed that the average mean of cadence, step length and walking speed for Parkinson's disease patients are lower than normal subjects, while the mean of stride time for Parkinson's disease patients are higher. Further, for kinematic parameter, overall joint angle of hip, knee and ankle mean values are lower for Parkinson's disease patients as compared to normal group. In addition, for kinetic parameter, all mean values of ground reaction force parameters are higher for normal subjects with walking speed contributed as the major determinant. To evaluate the significant features that could be used as identification between PD and normal subjects, statistical analysis is conducted. Hence, based on the statistical analysis results, it was found that step length, walking speed, knee angle as well as vertical parameter of ground reaction force are the four significant features as indicators for classification of subject with Parkinson's disease based on the accuracy attained with Artificial Neural Network as classifier.

A statistical approach for orchid disease identification using RGB color

“…This plot can be used to indicate errors or uncertainty within the extracted features. Moreover, error plot can point out level of measurement accuracy might be [8] & [9]. Also, error plots can be used to visually compare between two quantities whether differences are statistically significant or otherwise.…”

Autism Spectrum Disorders Gait Identification Using Ground Reaction Forces

“…The time components of the 3D GRF were normalized to the percentage of stance phase time, whereas the 3D GRF amplitudes were normalized to the percentage of the participant's body weight [24,25]. Normalization steps were essentially performed to eliminate variations among the participants with different height, body mass, and duration of stance phase [26,27].…”

Évaluation d'un risque de chute selon les paramètres de la démarche et étude d'une méthode de transmission à l'aide de stimuli tactiles /

“…De telles méthodes sont utilisées pour différentier la démarche entre un sujet normal et un patient atteint de la maladie de parkinson [64]. Dans un même ordre d'idée, l'utilisation de réseaux de neurones artificielles permet l'identification de démarches anormales chez les parkinsoniens [65]. …”