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 …

With the recent development of microelectromechanical systems (MEMS), inertial sensors
have become widely used in the research of wearable gait analysis due to several factors …

Compared to other biometrics, gait is difficult to conceal and has the advantage of being
unobtrusive. Inertial sensors, such as accelerometers and gyroscopes, are often used to …

The scientific literature on automated gait analysis for human recognition has grown
dramatically over the past 15 years. A number of sensing modalities including those based …

There has been a growing interest in equip** the objects and environment surrounding
the user with sensing capabilities. Smart indoor spaces such as smart homes and offices …

In the digital world of today, global security issues have given rise to video surveillance
devices. Gait-based human recognition is an emerging behavioral biometric trait for …

Gait recognition plays a special role in visual surveillance due to its unique advantage, eg,
long-distance, cross-view and non-cooperative recognition. However, it has not yet been …

The electroencephalogram (EEG) signals are commonly used for diagnosis of epilepsy. In
this paper, we present a new methodology for EEG-based automated diagnosis of epilepsy …

Gait, the walking pattern of individuals, is one of the important biometrics modalities. Most of
the existing gait recognition methods take silhouettes or articulated body models as gait …

This work evaluates the security strength of a smartphone-based gait recognition system
against zero-effort and live minimal-effort impersonation attacks under realistic scenarios …