The essential human gait parameters are briefly reviewed, followed by a detailed review of
the state of the art in deep learning for the human gait analysis. The modalities for capturing …

Inertial sensors are included in most of the current smart devices and many researchers
have identified their ability to be used for analyzing different parameters of human behavior …

Wearable sensors have been proposed as alternatives to traditional laboratory equipment
for low-cost and portable real-time gait analysis in unconstrained environments. However …

We present a method to improve the accuracy of a zero-velocity-aided inertial navigation
system (INS) by replacing the standard zero-velocity detector with a long short-term memory …

Annotation of foot-contact and foot-off events is the initial step in post-processing for most
quantitative gait analysis workflows. If clean force plate strikes are present, the events can …

Inertial measurement units (IMUs) are commonly used for localization or movement tracking
in pervasive healthcare-related studies, and gait analysis is one of the most often studied …

Accurate stride-length estimation is a fundamental component in numerous applications,
such as pedestrian dead reckoning, gait analysis, and human activity recognition. The …

Convolutional neural networks (CNNs) have been widely adopted for computer vision
applications. CNNs require many multiplications, making their use expensive in terms of …

Background The use of miniaturized magneto-inertial measurement units (MIMUs) allows for
an objective evaluation of gait and a quantitative assessment of clinical outcomes. Spatial …

Robust gait segmentation is the basis for mobile gait analysis. A range of methods have
been applied and evaluated for gait segmentation of healthy and pathological gait bouts …