This paper addresses a methodology for the analysis of human gait, based on data acquired by means depth sensors. is dedicated to healthcare-related applications and involves identification phases gait cycle thresholding estimates velocities examined person’s feet. In order assess its performance, series experiments was carried out using reference gait-analysis system pressure-distribution-meas...

Gait analysis is the systematic study of human walking. It is helpful in the medical management of those diseases which affect the locomotion systems. Recently, the gait motion capture systems are becoming widely used by doctors and physical therapists for kinematics analysis and biomechanics and motion capture research, sports medicine and physical therapy, including human gait analysis and in...

A predictive forward-dynamic simulation of human gait would be extremely useful to many different researchers, and professionals. Metabolic efficiency is one of the defining characteristics of human gait. Forward-dynamic simulations of human gait can be used to calculate the muscle load profiles for a given walking pattern, which in turn can be used to estimate metabolic energy consumption. One...

Robots that can recognize emotions can improve humans’ mental health by providing empathy and social communication. Emotion recognition by robots is challenging because unlike in human-computer environments, facial information is not always available. Instead, our method proposes using speech and gait analysis to recognize human emotion. Previous research suggests that the dynamics of emotional...

Gait and static body measurement are important biometric technologies for passive human recognition. Many previous works argue that recognition performance based completely on the gait feature is limited. The reason for this limited performance remains unclear. This study focuses on human recognition with gait feature obtained by Kinect and shows that gait feature can effectively distinguish fr...

In this paper we propose a new framework for age classification based on human gait using Hidden Markov Model (HMM). A gait database including young people and elderly people is built. To extract appropriate gait features, we consider a contour related method in terms of shape variations during human walking. Then the image feature is transformed to a lower-dimensional space by using the Frame ...

We describe an automated system that classifies gender by utilising a set of human gait data. The gender classification system consists of three stages: i) detection and extraction of the moving human body and its contour from image sequences; ii) extraction of human gait signature by the joint angles and body points; and iii) motion analysis and feature extraction for classifying gender in the...

Gait recognition provides the opportunity to identify different walking styles of people without physical intervention. However, covariates such as changing clothes and carrying conditions may influence accuracy. Our objective was patterns for through analyzing images from publicly available data set CASIA-B on gait. On dataset, proposed method evaluated by using GEI (gait energy image) inputs ...