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 …

In this paper we present the findings of a systematic literature review covering the articles
published in the last two decades in which the authors described the application of a …

The integration of wearable and wireless inertial body sensors with machine learning offers
the capacity to diagnose neurological disorders involving gait. Clinical rating scales may be …

Although machine learning is not yet being used in clinical practice within the fields of
prosthetics and orthotics, several studies on the use of prosthetics and orthotics have been …

To be an effective research and development engineer for the domain of the transtibial
powered prostheses, one needs a broad knowledge base, creativity, and compassion. The …

This study discussed application of a machine learning approach (Support vector machine,
SVM) for the automatic cognition of gait changes due to scoliosis using gait measures …

This paper focuses on gait abnormality type identification—specifically, recognizing antalgic
gait. Through experimentation, we demonstrate that detecting an individual's gait type is a …

Artificial intelligence and machine learning are helping people and businesses achieve key
goals, obtain actionable insights, drive critical decisions, and create exciting, new, and …

Upper limb rehabilitation is an effective methodology to restore and improve the functionality
of patients after multiple medical events, such as strokes, arthroscopic surgery, and breast …

Assessment methods in human locomotion often involve the description of normalised
graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches …