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

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      Author
      Erden, F.
      Velipasalar, S.
      Alkar, A. Z.
      Çetin, A. Enis
      Date
      2016-03
      Source Title
      IEEE Signal Processing Magazine
      Print ISSN
      1053-5888
      Publisher
      Institute of Electrical and Electronics Engineers
      Volume
      33
      Issue
      2
      Pages
      36 - 44
      Language
      English
      Type
      Article
      Item Usage Stats
      130
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      281
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      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.
      Keywords
      Sensor systems
      Vibrations
      Intelligent sensors
      Senior citizens
      Fires
      Monitoring
      Permalink
      http://hdl.handle.net/11693/49279
      Published Version (Please cite this version)
      https://doi.org/10.1109/MSP.2015.2489978
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      • Department of Electrical and Electronics Engineering 3524
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