Advances in machine learning and contactless sensors have given rise to ambient
intelligence—physical spaces that are sensitive and responsive to the presence of humans …

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 …

Various medical systems exist for monitoring people in daily life, but they typically require
the patient to wear a device, which can create discomfort and can limit long-term use …

Radar-based activity recognition is a problem that has been of great interest due to
applications such as border control and security, pedestrian identification for automotive …

Radar is considered an important technology for health monitoring and fall detection in
elderly assisted living due to a number of attributes not shared by other sensing modalities …

Falling or tripping among elderly people living on their own is recognized as a major public
health worry that can even lead to death. Fall detection systems that alert caregivers, family …

In this paper, we propose an approach that uses deep learning to detect a human fall. The
proposed approach automatically captures the intricate properties of the radar returns. In …

This paper reviews recent works in the literature on the use of systems based on radar and
RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research …

An aging population is increasingly prevalent in both developed and developing countries,
raising a series of social challenges and economic burdens. In particular, more elderly …

Automatic detection of a falling person based on noncontact sensing is a challenging
problem with applications in smart homes for elderly care. In this article, we propose a radar …