Sensors in assisted living: a survey of signal and image processing methods

Abstract

Our society will face a notable demographic shift in the near future. According to a United Nations report, the ratio of the elderly population (aged 60 years or older) to the overall population increased from 9.2% in 1990 to 11.7% in 2013 and is expected to reach 21.1% by 2050 [1]. According to the same report, 40% of older people live independently in their own homes. This ratio is about 75% in the developed countries. These facts will result in many societal challenges as well as changes in the health-care system, such as an increase in diseases and health-care costs, a shortage of caregivers, and a rise in the number of individuals unable to live independently [2]. Thus, it is imperative to develop ambient intelligence-based assisted living (AL) tools that help elderly people live independently in their homes. The recent developments in sensor technology and decreasing sensor costs have made the deployment of various sensors in various combinations viable, including static setups as well as wearable sensors. This article presents a survey that concentrates on the signal processing methods employed with different types of sensors. The types of sensors covered are pyro-electric infrared (PIR) and vibration sensors, accelerometers, cameras, depth sensors, and microphones.