| Title: | Perspective chapter: recognition of activities of daily living for elderly people in the era of digital health |
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| Authors: | ID Sepesy Maučec, Mirjam (Author)
ID Donaj, Gregor (Author) |
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| Files: |  1183909.pdf (3,13 MB)
MD5: 7CE576F2560BEDA1A23AAA6A3D287917
 https://www.intechopen.com/chapters/1183909
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.16 - Independent Scientific Component Part or a Chapter in a Monograph |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
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| Abstract: | People around the world are living longer. The question arises of how to help
elderly people to live longer independently and feel safe in their homes. Activity of
Daily Living (ADL) recognition systems automatically recognize the daily activities of
residents in smart homes. Automated monitoring of the daily routine of older individuals, detecting behavior patterns, and identifying deviations can help to identify
the need for assistance. Such systems must ensure the confidentiality, privacy, and
autonomy of residents. In this chapter, we review research and development in the
field of ADL recognition. Breakthrough advancements have been evident in recent
years with advances in sensor technology, the Internet of Things (IoT), machine
learning, and artificial intelligence. We examine the main steps in the development of
an ADL recognition system, introduce metrics for system evaluation, and present the
latest trends in knowledge transfer and detection of behavior changes. The literature
overview shows that deep learning approaches currently provide promising results.
Such systems will soon mature for more diverse practical uses as transfer learning
enables their fast deployment in new environments. |
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| Keywords: | digital health, elderly, activities of daily living, recognition of activities, sensors, machine learning |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 17.01.2024 |
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| Publication date: | 10.04.2024 |
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| Publisher: | IntechOpen |
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| Year of publishing: | 2024 |
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| Number of pages: | str. 29-46 |
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| PID: | 20.500.12556/DKUM-96509  |
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| UDC: | 004.5 |
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| COBISS.SI-ID: | 215910147 |
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| DOI: | 10.5772/intechopen.1004532 |
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| Copyright: | © 2024 The Author(s) |
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| Publication date in DKUM: | 15.01.2026 |
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| Views: | 133 |
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| Downloads: | 3 |
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| Metadata: |    |
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| Categories: | Misc.
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