Ambient Assisted Living

Multi-Resident Human Behaviour Identification in Ambient Assisted Living Environments

Multimodal interactions in ambient assisted living environments require human behaviour to be recognized and monitored automatically. The complex nature of human behaviour makes it extremely difficult to infer and adapt to, especially in …

ARAS Human Activity Datasets in Multiple Homes with Multiple Residents

The real world human activity datasets are of great importance in development of novel machine learning methods for automatic recognition of human activities in smart environments. In this study, we present the details of ARAS (Activity Recogni­tion …

A smart couch design for improving the quality of life of the patients with cognitive diseases

In this paper, we focus on the human activity recognition module of a homecare system that consists of wireless sensors developed for remotely monitoring patients with cognitive disorders, such as Alzheimer. To this end, as an initial study, we …

Using Active Learning to Allow Activity Recognition on a Large Scale

Automated activity recognition systems that use probabilistic models require labeled data sets in training phase for learning the model parameters. The parameters are different for every person and every environment. Therefore, for every person or …

Wireless Healthcare Monitoring with RFID-Enhanced Video Sensor Networks

In pervasive healthcare systems, WSNs provide rich contextual information and alerting mechanisms against odd conditions with continuous monitoring. Furthermore, they minimize the need for caregivers and help the chronically ill and elderly to …

WeCare: Wireless Enhanced Healthcare

In-home pervasive healthcare systems provide rich contextual information and alerting mechanisms against odd conditions with continuous monitoring. This minimizes the need for caregivers and help the chronically ill and elderly to survive an …

Wireless Sensor Networks for Healthcare: A survey

A Robust Multimodal Fall Detection Method for Ambient Assisted Living Applications

Accidental falls threaten the lives of people over 65 years of age and can be overcome with quick action for saving lives. Old people who live alone and those who have chronic diseases constitute the main risk groups. Fast and effective detection of …

Multi-modal Fall Detection Within the WeCare Framework

Falls are identified as a major health risk for the elderly and a major obstacle to independent living. Considering the remarkable increase in the elderly population of developed countries, methods for fall detection have been a recent active area of …

Using Wireless Sensor Network Technologies for Elder and Child Care: An Application Architecture Proposal

For the last decade wireless sensors, especially multi-modal sensor technologies have been developing for supporting healthcare services for elderly and children. The main motivation behind this is the fact that the world’s expectations for an …