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Design of Care Decision Support System Based on Home-Based Behavior of Elderly: A Design Science Study

Author

Listed:
  • Dong Kong
  • Yanli Wang
  • Kai Sun

Abstract

With the development of Information Technology and Internet of Things, using unobtrusive sensors to monitor the home-based behavior of the elderly, and assisting the care givers to make care decisions based on this data plays an important role in ensuring the health and safety of the elderly living alone. Adopting the Design Science Approach, this study designs, implements, and evaluates a care decision support system based on home-based behavior of elderly. This system preprocesses the behavior data collected by sensors and divides it into Instantaneous Behavior data and Continuous Behavior data. Adopting Multivariate Gaussian Model and Topic Model, this system automatically provides the visualized results of overall analysis, baseline analysis, and long-term analysis. It can assist caregivers in finding early signs threatening elderly’s health and safety, and making care decisions. Three caregivers with more than 1-year relevant experience participates in the evaluation, and the results indicate that the system designed in this paper has more support effectiveness. This system provides a more effective tool of supporting caregivers making decisions for elderly living alone.

Suggested Citation

  • Dong Kong & Yanli Wang & Kai Sun, 2022. "Design of Care Decision Support System Based on Home-Based Behavior of Elderly: A Design Science Study," SAGE Open, , vol. 12(1), pages 21582440221, March.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:1:p:21582440221086606
    DOI: 10.1177/21582440221086606
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    References listed on IDEAS

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    1. Bin Zhu & Stephanie A. Watts, 2010. "Visualization of Network Concepts: The Impact of Working Memory Capacity Differences," Information Systems Research, INFORMS, vol. 21(2), pages 327-344, June.
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