Background falls and fall-related injuries are common in older adults, have negative effects
on functional independence and quality of life and are associated with increased morbidity …

Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Numerous studies have focused on making telemedicine smart through the Internet of
Things (IoT) technology. These works span a wide range of research areas to enhance …

Falls, especially in elderly persons, are an important health problem worldwide. Reliable fall
detection systems can mitigate negative consequences of falls. Among the important …

Fall causes trauma or critical injury among the geriatric population which is a second
leading accidental cause of post-injury mortality around the world. It is crucial to keep elderly …

Abstract In Artificial Intelligence, Human Activity Recognition (HAR) refers to the capability of
machines to identify various activities performed by the users. The knowledge acquired from …

Recognizing human activities and monitoring population behavior are fundamental needs of
our society. Population security, crowd surveillance, healthcare support and living …

This paper compares the three levels of data fusion with the goal of determining the optimal
level of data fusion for multi-sensor human activity data. Using the data processing pipeline …

Fall detection is a very important challenge that affects both elderly people and the carers.
Improvements in fall detection would reduce the aid response time. This research focuses …

Unintentional falls can cause severe injuries and even death, especially if no immediate
assistance is given. A fall detection system aims to detect a fall as soon as it occurs …