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A Novel Data Mining Method on Falling Detection and Daily Activities Recognition
Donghua University, Shanghai, China.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. STC. (Sensor Network & Security)
Donghua University, Shanghai, China.
Donghua University, Shanghai, China.
2015 (English)In: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, IEEE Computer Society, 2015, 675-681 p., 7372198Conference paper, Published paper (Refereed)
Abstract [en]

With the intensification of aging population, a growing number of elderly people have to live alone due to domestic and social reasons. Falling becomes one of the most crucial factors in threatening the elderly's lives, which is always difficult to be detected as it is instantaneous and easy to be confused with other motions, such as lying down. In this paper, a new method is proposed for accurate falling detection and activities recognition. It applies hierarchical classifiers to the time series data set including eleven activities of daily living (ADLs), collected by four wearable sensors. The new method combines two machine learning algorithms, performs concrete analysis on the original outcome and then obtains several scarcely-confused groups separately. The experiment indicates that the new method improves the accuracy of classification to a larger extent, reached to more than 90%. Furthermore, the matched algorithm for applying these classifiers, called Hierarchical Classifier Algorithm (HCA), is proposed as well.

Place, publisher, year, edition, pages
IEEE Computer Society, 2015. 675-681 p., 7372198
Keyword [en]
Falling detection, Hierarchical Classifier Algorithm (HCA), Machine learning algorithm, Wearable sensor
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:miun:diva-26418DOI: 10.1109/ICTAI.2015.102ISI: 000374592500087Scopus ID: 2-s2.0-84963611994Local ID: STCOAI: oai:DiVA.org:miun-26418DiVA: diva2:881974
Conference
27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), november 9-11, 2015, Vietri sul Mare, Italy
Funder
Knowledge Foundation, 20140321
Available from: 2015-12-12 Created: 2015-12-12 Last updated: 2016-12-23Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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