Fall detection systems are crucial for identifying falls and ensuring timely assistance, thus
reducing the risk of serious injuries. With the development of society and increasing …

Multimodal data fusion is a critical element of fall detection systems, as it provides more
comprehensive information than single-modal data. Yet, data heterogeneity between …

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 …

As the population ages, health issues like injurious falls demand more attention. One
solution is to use wearable devices to detect falls. Nevertheless, most of these devices raise …

Human falls occur rarely; however, they can lead to severe consequences if not addressed
immediately. With the rise of nuclear families, there has been a significant increase in the …

RF sensing offers an unobtrusive, user-friendly, and privacy-preserving method for detecting
accidental falls and recognizing human activities. Contemporary RF-based HAR systems …

It is necessary to detect the fall of the elderly in time. As a noncontact monitoring device,
radar can monitor users without their knowledge and protect their privacy. The unsupervised …

The technology for human activity recognition has diverse applications within the Internet of
Things spectrum, including medical sensing, security measures, smart home systems, and …

Falls can be one of the most damaging events that elders may experience in their lives,
especially when they live alone. The impact of a fall can vary from minor bruises, to life …

Emitter classification plays a crucial role in electronic support measurement systems. A data-
driven model named Gaussian dynamic recurrent unit is proposed to accomplish the end-to …