Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …

Falls among older adults substantially affect mobility, health, and mortality. However,
advancements in wireless and internet-of-things technologies have led to the development …

Seniors who live alone at home are at risk of falling and injuring themselves and, thus, may
need a mobile robot that monitors and recognizes their poses automatically. Even though …

Falls pose a significant risk to elderly people, patients with diseases such as neurological
disorders, cardiovascular diseases, and disabled children. This highlights the need for real …

Recent advancements in the Internet of Medical Things (IoMT) have revolutionized the
healthcare sector, making it an active research area in the academic and industrial sectors …

Implementing skeleton-based action recognition in real-world applications is a difficult task,
because it involves multiple modules such as person detection and pose estimaton. In terms …

Falls pose a major threat for the elderly as they result in severe consequences for their
physical and mental health or even death in the worst-case scenario. Nonetheless, the …

Unintentional human falls, particularly in older adults, can result in severe injuries and
death, and negatively impact quality of life. The World Health Organization (WHO) states that …

As the proportion of elderly individuals in developed countries continues to rise globally,
addressing their healthcare needs, particularly in preserving their autonomy, is of paramount …

In the realm of sustainable IoT and AI applications for the well-being of elderly individuals
living alone in their homes, falls can have severe consequences. These consequences …