Classifying pathological gaits is crucial for identifying impairments in specific areas of the
human body. Previous studies have extensively employed machine learning and deep …

Purpose The traditional failure mode and effect analysis (FMEA) has some limitations, such
as the neglect of relevant historical data, subjective use of rating numbering and the less …

Human gait is an important biometric trait which is used in a variety of applications. The
development of low-cost inertial sensors has facilitated the capturing of human gait …

Abstract Analysis of walking-related pathologies can be done using low-cost wearable
sensors that could be perceived as efficient and plausible methods for identifying gait …

It is crucial to find methods that analyze large amount of data captured by cameras and/or
various sensors installed all around us. Machine learning becomes a prevailing tool in …

Wearable sensor-based gait recognition has received much interest because it is
unobtrusive and is user friendly. Many research has been carried out in this area but …

Gait recognition is an emerging biometric method that allows an automatic verification of a
person by the way he or she walks. This paper presents a new dataset for gait recognition …

Structured gait patterns are currently used as a biometric technique to recognize individuals
and in building appropriate exoskeleton technologies. In this study, the features involved in …

Neurological diseases such as Parkinson's disease (PD) are becoming a major problem
worldwide due to increasing longevity and the resulting aging population. Since PD is …

Recent advances in low-cost wearable sensors with methodologies, have opened up a
promising future for gait analysis. By providing patient analysis with gait disorders from …