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Toward Sentiment Analysis in Elderly Care Facility

  • Ken FukudaEmail author
  • Satoshi Nishimura
  • Huizhi Liang
  • Takuichi Nishimura
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10247)

Abstract

Hand-over notes are extremely important to share information about irregular incidents at elderly care facilities and provide high-quality services. However, taking notes is a time-consuming task. Moreover, handwritten hand-over notes make it difficult to pass on experience and related know-how to other workers. To curate that field community intelligence, a handover support system for elderly care facilities was installed into a facility and evaluated. The system is now in actual operation at the care facility. The authors aim to use handover support system as a communication tool that sense the feelings of the care workers and supports them to maintain motivation and cultivate self-directedness. To realize this aim, this paper reports the results of hand-over data analysis and comparison with traditional paper-based hand-over notes. Furthermore, the authors explored the possibility of applying sentiment analysis technology to hand-over messages to sense the atmosphere of their working environment.

Keywords

Information share Elderly care Text mining Sentiment analysis 

Notes

Acknowledgment

This study was partly conducted under the support of “Fundamental Research For Human Centered Service Engineering”, the development and demonstration testing of next-generation, highly reliable, energy-saving core IT technologies (Service Engineering R & D field) a commissioned project for FY 2011 by the Ministry of Economy, Trade and Industry (METI) of Japan, the “Project to Promote the Development and Introduction of Robotic Devices for Nursing Care” by METI, and Grants-in-Aid for Scientific Research (Subject number: 24500676). This study was partly supported by Japanese METI’s Robotic Care Equipment Development and Introduction Project,NEDO’s Artificial Intelligence Research Project. The authors extend their gratitude to Long-Term Care Health Facility Wakoen of Social Medical Care Corporation Tosenkai for cooperation in development and evaluation of the system.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ken Fukuda
    • 1
    Email author
  • Satoshi Nishimura
    • 1
  • Huizhi Liang
    • 1
  • Takuichi Nishimura
    • 1
  1. 1.AI Research CenterNational Institute of Advanced Industrial Science and TechnologyTokyoJapan

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