A number of review or survey articles have previously appeared on human action
recognition where either vision sensors or inertial sensors are used individually …

Background wearable sensors are often used to acquire data for gait analysis as a strategy
to study fall events, due to greater availability of acquisition platforms, and advances in …

Gesture recognition using machine-learning methods is valuable in the development of
advanced cybernetics, robotics and healthcare systems, and typically relies on images or …

In metaverse, a digital‐twin smart home is a vital platform for immersive communication
between the physical and virtual world. Triboelectric nanogenerators (TENGs) sensors …

Falling, as one of the main harm threats to the elderly, has drawn researchers' attentions and
has always been one of the most valuable research topics in the daily health-care for the …

During recent years, channel attention has attracted great interest in deep learning
community. Despite significant success, it has been rarely exploited in ubiquitous human …

The increase in elderly population especially in the developed countries and the number of
elderly people living alone can result in increased healthcare costs which can cause a huge …

Human action recognition is used in many applications such as video surveillance, human-
computer interaction, assistive living, and gaming. Many papers have appeared in the …

Falls are an important healthcare problem for vulnerable persons like seniors. Response to
potential emergencies can be fastened timely detection and classification of falls. This paper …

Recognition of human movements is very useful for several applications, such as smart
rooms, interactive virtual reality systems, human detection and environment modeling. The …