We systematically reviewed observational and clinical trials (baseline) studies examining
differences in gait parameters between Parkinson's disease (PD) in on-medication state and …

Wearable technology comprises miniaturized sensors (eg, accelerometers) worn on the
body and/or paired with mobile devices (eg, smart phones) allowing continuous patient …

Background Although digital mobility outcomes (DMOs) can be readily calculated from real-
world data collected with wearable devices and ad-hoc algorithms, technical validation is …

Introduction: The present review aims to provide an overview of the most common uses of
wearable inertial sensors in the field of clinical human movement analysis. Areas covered …

Gait assessment is an essential tool for clinical applications not only to diagnose different
neurological conditions but also to monitor disease progression as it contributes to the …

Background The quantification of gait temporal parameters (ie step time, stance time) is
crucial in human motion analysis and requires the accurate identification of gait events (ie …

Machine learning methods have been widely used for gait assessment through the
estimation of spatio-temporal parameters. As a further step, the objective of this work is to …

Introduction Existing mobility endpoints based on functional performance, physical
assessments and patient self-reporting are often affected by lack of sensitivity, limiting their …

Joint kinematics is typically limited to the laboratory environment, and the restricted volume
of capture may vitiate the execution of the motor tasks under analysis. Conversely, clinicians …

Abstract Background Inertial measurement units (IMUs) offer the ability to measure walking
gait through a variety of biomechanical outcomes (eg, spatiotemporal, kinematics, other) …