Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

The functional gait problems encountered by stroke patients include impaired balance, abnormal gait pattern with marked asymmetry, pathological trunk and spinal motion. Many different methods of physiotherapy are used to improve functional ability (especially gait) in stroke patients, but their efficacy and outcome are often not objectively assessed. The goal of this paper is to compare two the...

‘Gait’ is a person’s manner of walking. Some patients may have an abnormal gait due to physical impairment. Clinical gait analysis (CGA) is a practical technique and procedure for identifying the underlying impairments that affect the pattern of a patient’s gait. The CGA is critical for further treatment planning. Essentially, CGA tries to use patients’ physical examination results, known as st...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...

Repetition in walking may vary from trial to trial: gait parameters are not constant but they rather fluctuate in the course of time and change from one stride to the next, even if environmental and external conditions are fixed. The aim of this study was to specify the effect of gait speed and gender on the variability of gait. The variability of spatialtemporal parameters was characterized by...

Gait in people with Parkinson’s disease (PD) is arrhythmic, small in amplitude, and variable (1–3). In addition, people with PD often exhibit reduced automaticity of movement (4), resulting in increased attention directed toward gait. This can be observed empirically when they have to perform a secondary task in addition to gait, so-called dual-task walking. In dual-task conditions, people with...

In this paper we describe a system for automatic gait analysis. Different kinds of human gait are recognized using sequences of grey–level images. No markers are needed to get the trajectories of different body parts. The tracking of body parts and the classification are based on statistical models. We model several body parts and the background as mixture densities. The positions are determine...

Gait sequence analysis from the input binary silhouettes, has various applications, such as person identification, human action recognition, event recognition and classification. The gait feature extraction is a key step in gait analysis. The ’Topic Model’, used for text classification, is one of the potential semantic approaches to study gait sequence analysis. The proposed algorithm uses Late...