With advances in medicine and healthcare systems, the average life expectancy of human
beings has increased to more than 80 yrs. As a result, the demographic old‐age …

This paper describes a wearable Fall Detection System (FDS) based on a body-area
network consisting of four nodes provided with inertial sensors and Bluetooth wireless …

Fall is a prominent issue due to its severe consequences both physically and mentally. Fall
detection and prevention is a critical area of research because it can help elderly people to …

The Internet of Things (IoT) technologies reserves a large latent capacity in dealing with the
emerging fall detection problem of elder people. The radar-based IoT methods are …

This study aims to comprehensively compare the accuracy and practicality of three different
types of algorithms for pre-impact fall detection using both young and old subjects …

Wearable devices are a trending topic in both commercial and academic areas. Increasing
demand for innovation has led to increased research and new products, addressing new …

Internet of Things (IoT) enabled geriatric healthcare systems have gained importance in the
recent years due to an increase in the number of elderly people living alone. The application …

The application of machine learning techniques to detect and classify falls is a prominent
area of research in the domain of intelligent assisted living systems. Machine learning (ML) …

Recognition of human activity is a significant area of research with numerous uses. In
developed countries, the rising age of citizens requires the improvement of the medical …

Intelligent IoT-based ambient assisted living systems (AALS) have been a major research
focus area in recent times. According to the studies conducted by the Govt. of India, elderly …