In this paper we suggest a novel method to approximate the fitness function of a genetic programming approach in order to develop fast and stable gait patterns for a quadruped robot. Therefore, gait patterns are classified by so called Signal Space Detectors. We show how a Signal Space Detector can extract information about the reliability of a classification. Finally, we demonstrate how this i...

Human gait decision was carried out with the help of similarity measure design. Gait signal was selected through hardware implementation including all in one sensor, control unit, and notebook with connector. Each gait signal was considered as high dimensional data. Therefore, high dimensional data analysis was considered via heuristic technique such as the similarity measure. Each human patter...

This paper presents a wearable wireless sensor system designed for real-time gait pattern analysis in glaucoma patients. Many clinical studies have reported that glaucoma patients experienced mobility issues such as walking slowly and bumping into obstacles frequently. The gait attributes of glaucoma patients, however, have not been studied in the literature. We design and develop a shoe-integr...

In this study, we analyse the electroencephalography (EEG) signal associated with gait speed changes (i.e. acceleration or deceleration). For data acquisition, healthy subjects were asked to perform volitional speed changes between 0, 1, and 2 Km/h, during treadmill walk. Simultaneously, the treadmill controller modified the speed of the belt according to the subject's linear speed. A classifie...

Multivariate gait data have traditionally been challenging to analyze. Part 1 of this review explored applications of fuzzy, multivariate statistical and fractal methods to gait data analysis. Part 2 extends this critical review to the applications of artificial neural networks and wavelets to gait data analysis. The review concludes with a practical guide to the selection of alternative gait d...

In this study, we focused on the gait of Parkinson’s disease (PD) and presented a gray box model for it. We tried to present a model for basal ganglia structure in order to generate stride time interval signal in model output for healthy and PD states. Because of feedback role of dopamine neurotransmitter in basal ganglia, this part is modelled by “Elman Network”, which is a neural network stru...

To test for an association between the LRRK2-G2019S mutation and gait, we studied 52 first-degree relatives of patients with Parkinson’s disease (PD) who carry this mutation. An accelerometer quantified gait during usualwalking, fast-walking, and dual-tasking. Noncarriers (n 1⁄4 27) and carriers (n1⁄4 25) were similar with respect to age, gender, height, and gait speed during all conditions. Du...

To test for an association between the LRRK2-G2019S mutation and gait, we studied 52 first-degree relatives of patients with Parkinson's disease (PD) who carry this mutation. An accelerometer quantified gait during usual-walking, fast-walking, and dual-tasking. Noncarriers (n = 27) and carriers (n = 25) were similar with respect to age, gender, height, and gait speed during all conditions. Duri...

in this study, we focused on the gait of parkinson’s disease (pd) and presented a gray box model for it. we tried to present a model for basal ganglia structure in order to generate stride time interval signal in model output for healthy and pd states. because of feedback role of dopamine neurotransmitter in basal ganglia, this part is modelled by “elman network”, which is a neural network stru...