Abstract Human Activity Recognition (HAR) has become a crucial element for smart
healthcare applications due to the fast adoption of wearable sensors and mobile …

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 …

With the advancement in the healthcare and medicine sector, now a day's average life span
of humans has increased. Due to an increase in average life expectancy, the demographic …

Health sector is a life critical domain, which requires fast and intelligent decisions. Artificial
intelligence-based monitoring systems can help the elderly people in situations like fall. In e …

Because falls are the second leading cause of injury deaths, especially in the elderly
according to WHO statistics, there have been a lot of studies on developing a fall detection …

Human Activity Recognition (HAR) has emerged as a potential research topic for smart
healthcare owing to the fast growth of wearable and smart devices in recent years. The …

Older adults who age in place face many health problems and need to be taken care of. Fall
is a serious problem among elderly people. In this paper, we present the design and …

In recent years, there has been an immense amount of research into fall event detection.
Generally, a fall event is defined as a situation in which a person unintentionally drops down …

Human activity recognition has played a crucial role in healthcare information systems due
to the fast adoption of artificial intelligence (AI) and the internet of thing (IoT). Most of the …

Smart expert systems line up with various applications to enhance the quality of lifestyle of
human beings, such as major applications for smart health monitoring systems. An …