Background Artificial intelligence (AI) holds the promise of supporting nurses' clinical
decision-making in complex care situations or conducting tasks that are remote from direct …

Ambient assisted living (AAL) systems need to understand the user's situation, which makes
activity recognition an important component. Falls are one of the most critical problems of the …

One of the essential tasks of healthcare and smart-living systems is to recognize the current
activity of a particular user. Such activity recognition (AR) is demanding when only limited …

The increasing size of the elderly population is driving the development of ambient assisted
living systems and telehealth. The recognition of the user's everyday activities and detection …

This demo paper presents the RAReFall system, which is a real-time activity recognition and
fall detection system. It is tuned for robustness and real-time performance by combining …

Habits characterize the activities of elderly people. Monitoring their habits and their ability to
carry out the activities of daily living is a great challenge in order to improve aging at home …

Real-time locating system (RTLS) based on UWB radio technology can be used to track
people performing every-day activities. However, the quality of obtained data is relatively …

The aging of the population in the coming decades raises new challenges in order to help
elderly people live longer at home, independently and safely. The emergence of assistive …

The idea for the iHELP project originates in 2011. Disturbing statistics related to
cardiovascular disease (ie 224 people a day die from sudden cardiac arrest in UK) made us …

This paper presents an intelligent system for elderly people care at home that has been
implemented and tested in real life environments. The expert system is based on the …