The hidden Markov models are statistical models used in many real-world applications and
communities. The use of hidden Markov models has become predominant in the last …

Background: Gait dysfunction or impairment is considered one of the most common and
devastating physiological consequences of stroke, and achieving optimal gait is a key goal …

We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …

Evidence-based medicine is the most prevalent paradigm adopted by physicians. Clinical
practice guidelines typically define a set of recommendations together with eligibility criteria …

Movement primitive segmentation enables long sequences of human movement
observation data to be segmented into smaller components, termed movement primitives, to …

Gait analysis for the patients with lower limb motor dysfunction is a useful tool in assisting
clinicians for diagnosis, assessment, and rehabilitation strategy making. Implementing …

Modeling and evaluation of patients' gait patterns is the basis for both gait assessment and
gait rehabilitation. This paper presents a convenient and real-time gait modeling, analysis …

Knee osteoarthritis (OA) is the most common joint disorder which results in mobility
impairment and altered gait patterns. For the purpose of developing an automatic and highly …

In the rehabilitation field, clinicians are continually struggling to assess improvements in
patients following interventions. In this paper, we propose an approach to use gait analysis …

Understanding the fine-grained temporal structure of human actions and its semantic
interpretation is beneficial to many real-world tasks, such as sports movements …