Recognition of human movements with radar for ambient activity monitoring is a developed
area of research that yet presents outstanding challenges to address. In real environments …

This paper presents a framework based on multilayer bi-LSTM network (bidirectional Long
Short-Term Memory) for multimodal sensor fusion to sense and classify daily activities' …

Human activity recognition (HAR) plays a vital role in many applications, such as
surveillance, in-home monitoring, and health care. Portable radar sensor has been …

Indoor human activity recognition is actively studied as part of creating various intelligent
systems with applications in smart home and office, smart health, internet of things, etc …

This paper presents different information fusion approaches to classify human gait patterns
and falls in a radar sensors network. The human gaits classified in this work are both …

Radar-based human motion and activity recognition is currently a topic of great research
interest, as the aging population increases and older individuals prefer an independent …

Recognizing movements during sleep is crucial for the monitoring of patients with sleep
disorders, and the utilization of ultra-wideband (UWB) radar for the classification of human …

Portable, low-cost, microwave radars have attracted researchers' attention for being an
alternative noncontact solution for structural condition monitoring. In addition, by leveraging …

In this paper, we propose a Multi-View Convolutional Neural Network and Long Short-Term
Memory (CNN-LSTM) network which fuses multiple “views” of the time-range-Doppler radar …

Advances and updates in medical applications utilizing microwave techniques and
technologies are reviewed in this paper. The article aims to provide an overview of enablers …