Human face/gait-based gender recognition has been intensively studied by the previous literatures, yet most of them are based on the same database. Although nearly perfect gender recognition rates can be achieved in the same face/gait dataset, they assume a closed-world and neglect the problems caused by dataset bias. Real-world human gender recognition system should be dataset-independent, i.e...

Human identification has recently gained growing interest from computer vision researchers. Gait recognition domain has a wide range of applications in medicine (biomechanics), mathematics, psychology, rehabilitation and sports activity. It has the unique capability to recognize people at a distance when other biometrics is obscured. This paper aims to handle high levels of occlusion, which is ...

Gait and face are two important biometrics for human identification. Complementary properties of these two biometrics suggest fusion of them. The relationship between gait and face in the fusion is affected by the subject-to-camera distance. On the one hand, gait is a suitable biometric trait for human recognition at a distance. On the other hand, face recognition is more reliable when the subj...

The purpose of this paper was to model the human gait of typical subjects and patients with such deformities of lower limbs as: spastic diplegia cerebral palsy and spina bifida occulta. Model coefficients will lead to the development of a better computer system to support clinical decision-making in human gait in terms of assessment, diagnosis, and classification. Human gait was evaluated by us...

We describe a new method for automatic gait recognition based on analysing the symmetry of human motion using the Generalised Symmetry Operator. This approach is reinforced by the psychologists view that gait is a symmetrical pattern of motion and results show that gait can indeed be recognised by symmetry analysis. 2003 Published by Elsevier Science B.V.

Exoskeletons are utilized extensively in robotic rehabilitation and power augmentation purposes. One of the most recognised control algorithms utilized in this field is the impedance controller. Impedance control approach provides the capability of realizing different rehabilitation exercises by tuning the target impedance gains. Trial and error experimental approach is one of the most common m...

INTRODUCTION Accelerometers are becoming an increasingly important tool in the study of human movement. Their ease and affordability, combined with the potential to collect large amounts of continuous data outside the laboratory setting makes them excellent tools for gait analysis. Research has demonstrated the effectiveness of a single tri-axial accelerometer in measuring mean spatiotemporal p...

We present a random walk, fractal analysis of the stride-to-stride fluctuations in the human gait rhythm. The gait of healthy young adults is scale-free with long-range correlations extending over hundreds of strides. This fractal scaling changes characteristically with maturation in children and older adults and becomes almost completely uncorrelated with certain neurologic diseases. Stochasti...

Key points Gait-related arm swing in humans supports efficient lower limb muscle activation, indicating a neural coupling between the upper and limbs during gait. Intermuscular coherence analyses of gait-related electromyography from 20 healthy participants identified significant alpha beta/gamma bands that share common subcortical cortical drivers coordinate rhythmic four-limb gait pattern. Ad...

We describe a new method for recognizing humans by their gait using back propagation neural network(BPNN), BPNN algorithm is used to recognize humans by their gait patterns. Automatic gait recognition using Fourier descriptors and independent component analysis (ICA) for the purpose of human identification at a distance. Firstly, a simple background generation algorithm is introduced to subtrac...