This paper describes an investigation into the biomechanical effects of load carriage dynamics on human locomotion performance. A whole body, inverse dynamics gait model has been developed which uses only kinematic input data to define the gait cycle. To provide input data, three-dimensional gait measurements have been conducted to capture whole body motion while carrying a backpack. A nonlinea...

Passive dynamic bipedal walking (PDW) is an attractive topic not only for robotics field but also the other scientific fields, i.e. physics and biology. In order to clarify its mechanism of walking, many researchers have developed various PDW machines. We also have developed several 3D PDW with flat feet and ankle springs. However there are no researches on the measurement of 3-D PDW gait, whic...

There are numerous causes that can affect the functioning of the human locomotor system, leading to the appearance of joint disorders in the lower limb and generating atypical gait patterns. The importance of research and development in assistance technologies to compensate pathological gait have been recognised since the beginning of the twentieth century and numerous challenges still lie ahea...

Physical changes such as leg length discrepancy, the addition of a mass at the distal end of the leg, the use of a prosthetic, and stroke frequently result in an asymmetric gait. This paper presents a metric that can potentially serve as a benchmark to categorize and differentiate between multiple asymmetric bipedal gaits. The combined gait asymmetry metric (CGAM) is based on modified Mahalanob...

Simulating human motion is a complex problem due to redundancy of the human musculoskeletal system. The concept of task-based dynamic motion prediction using singleor multi-objective optimization techniques provides a viable approach for predicting dynamic gait motions of digital humans, subjected to basic physical and kinematical constraints. The task-based motion prediction is in fact a numer...

Human motion analysis has received a great attention from researchers in the last decade due to its potential use in different applications. We propose a new approach to extract human joints (Vertex positions)using a model-based method. The gait pattern is incorporated to aid the extraction process, where model templates are established through analysis of gait motion. People walk normal to the...

This paper describes a representation of gait appearance for the purpose of person identification and classification. This gait representation is based on simple features such as moments extracted from orthogonal view video silhouettes of human walking motion. Despite its simplicity, the resulting feature vector contains enough information to perform well on human identification and gender clas...

The aim of this work is to use Self Organizing Map (SOM) for clustering of locomotion kinetic characteristics in normal and Parkinson’s disease. The classification and analysis of the kinematic characteristics of human locomotion has been greatly increased by the use of artificial neural networks in recent years. The proposed methodology aims at overcoming the constraints of traditional analysi...

Human gait has become an important biometric in recent years. A silhouette based method is suggested in this paper, to recognize human in video by their gait. We used averaged silhouette to represent the gait cycle. Principal Component Analysis has been used to reduce the dimensionality of the features. We applied Euclidean distance to measure the similarity of the averaged silhouettes. We impl...

Human gait or walking manner is a biometric feature that allows identification of a person when other biometric features such as the face or iris are not visible. In this paper, we present a new pose-based convolutional neural network model for gait recognition. Unlike many methods that consider the full-height silhouette of a moving person, we consider the motion of points in the areas around ...