Background automatic recognition of human movement is an effective strategy to assess
abnormal gait patterns. Machine learning approaches are mainly applied due to their ability …

Gait disorders are common in neurodegenerative diseases and distinguishing between
seemingly similar kinematic patterns associated with different pathological entities is a …

This paper investigated application of a machine learning approach (Support vector
machine, SVM) for the automatic recognition of gait changes due to ageing using three types …

Human biomechanics and gait form an integral part of life. The gait analysis involves a large
number of interdependent parameters that were difficult to interpret due to a vast amount of …

Objective: This paper describes how non-invasive wearable sensors can be used in
combination with deep learning to classify artificially induced gait alterations without the …

Automated recognition of gait pattern change is important in medical diagnostics as well as
in the early identification of at-risk gait in the elderly. We evaluated the use of Kernel-based …

This paper reviews the recent literature on technologies and methodologies for quantitative
human gait analysis in the context of neurodegenerative diseases. The use of technological …

This paper proposes a comprehensive investigation of the automatic classification of
functional gait disorders (GDs) based solely on ground reaction force (GRF) measurements …

Human movements are characterized by highly non-linear and multi-dimensional
interactions within the motor system. Therefore, the future of human movement analysis …

An automated gait classification method is developed in this study, which can be applied to
analysis and to classify pathological gait patterns using 3D ground reaction force (GRFs) …