Analysis of daily-living dynamics

  • Authors:

  • Boštjan Kaluža;Matjaž Gams

  • Affiliations:

  • Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana, Slovenia and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia;Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana, Slovenia and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

  • Venue:
  • Journal of Ambient Intelligence and Smart Environments - Home-based Health and Wellness Measurement and Monitoring
  • Year:
  • 2012

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Abstract

Analysis of daily-living behavior is an important approach to assess the wellbeing of an elderly person that lives at home alone. This paper presents an approach to monitoring an individual in the home environment by an ambient-intelligence system in order to detect anomalies in daily-living patterns. The proposed method is based on transforming the sequence of posture and spatial information using a novel matrix presentation to extract spatial-activity features. Then, an outlier-detection method is used for a classification of the individual's usual and unusual daily patterns regardless, of the cause of the problem, be it physical or mental. Experiments indicate that the proposed algorithm successfully discriminates between the daily behavior patterns of a healthy person and those with health problems.