Sensors in Assisted Living: A survey of signal and image processing methods

Abstract

ur 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.

Remote patient monitoring: a comprehensive study

“…general health monitoring systems). Erden et al (2016) has done a very recent survey on sensors used in assisted living. In this review, the focus is on signal and image processing methods used in recent systems.…”

homeSound: Real-Time Audio Event Detection Based on High Performance Computing for Behaviour and Surveillance Remote Monitoring

“…The collection of data has been usually performed by infrared motion sensors, RFID, pressure sensors, smart tiles, cameras, ultrasound sensors, microphones and magnetic switches. The reader is referred to [22] for a recent survey presenting a complete insight to the different types of sensors in the context of AAL. Several projects have been conducted within the AAL framework, and we have classified them to be named in function of their final goal.…”

Feature diversity for fall detection and human indoor activities classification using radar systems

“…Irregularities and anomalies in these patterns could inform carers and health professionals on risks related to deteriorating physical and cognitive capabilities. Many different types of sensors and technologies have been suggested for this purpose, namely wearable devices such as accelerometers, inertial sensors, and panic buttons, infrared proximity sensors, magnetic and acoustic sensors, videocameras, RGB-Depth sensors, and radar sensors [3][4][5][6][7]. The interest in radar technologies for indoor monitoring is related to their contactless sensing capabilities, with no need for the users to wear or carry devices or change their habits, and to the insensitivity to light conditions in the environment where the monitored subjects operate.…”