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Survey of Smart Technologies for Fall Motion Detection: Techniques, Algorithms and Tools

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Advances in Information Technology (IAIT 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 344))

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Abstract

The aging population has become a world-wide social concern. The number of people living alone and experiencing falls is increasing. This is a major health risk, especially among the elderly; thus, the early detection of fall motion is of great significance. A smart home care system is needed to monitor abnormal events. This paper first conducts a survey of existing smart systems and techniques in detecting fall motion in human movement, including the emergence of new natural user interface (NUI) devices and systems in the consumer market. Secondly, the paper categorizes smart technologies for fall motion detection into three main technological groups: acoustic and ambient sensor-based, kinematic sensor-based, and lastly the computer vision and NUI. An insightful discussion of each category’s advantages and disadvantages is provided. The findings show a promising research direction of integrating the computer vision with the novel consumer-grade NUI device, such as Kinect, in achieving of an affordable and practical smart home fall motion detection system.

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Authors and Affiliations

  1. School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Orasa Patsadu, Chakarida Nukoolkit & Bunthit Watanapa

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  1. Orasa Patsadu
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  2. Chakarida Nukoolkit
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  3. Bunthit Watanapa
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Editors and Affiliations

  1. School of Information Technology, King Mongkut’s University of Technology Thonburi, 126 Pracha-U-This Td., Bangmod, Thungkru, 10140, Bangkok, Thailand

    Borworn Papasratorn , Nipon Charoenkitkarn  & Wichian Chutimaskul ,  & 

  2. School of Information Technology, King Mongkut’s University of Technology Thonburi, 126 Pracha-U-Thit Rd., Bangmod, Thungkru, 10140, Bangkok, Thailand

    Kittichai Lavangnananda  & Vajirasak Vanijja  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Patsadu, O., Nukoolkit, C., Watanapa, B. (2012). Survey of Smart Technologies for Fall Motion Detection: Techniques, Algorithms and Tools. In: Papasratorn, B., Charoenkitkarn, N., Lavangnananda, K., Chutimaskul, W., Vanijja, V. (eds) Advances in Information Technology. IAIT 2012. Communications in Computer and Information Science, vol 344. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35076-4_13

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  • DOI: https://doi.org/10.1007/978-3-642-35076-4_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35075-7

  • Online ISBN: 978-3-642-35076-4

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