Skip to main content
SpringerLink
Log in

A Framework of Personal Data Analytics for Well-Being Oriented Life Support

  • Conference paper
  • First Online:
Advanced Multimedia and Ubiquitous Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 354))

Abstract

Nowadays, we are living in a well-suited social environment with a variety of lifestyles and values. Life support has become important in such a diversified society. Along with continuously collecting the tremendous amount of personal big data generated in the social environment, it is possible for us to provide the life support based on personal data analytics. Moreover, analyzing such a kind of data can facilitate deep understanding of individual life. In this study, we focus on personal data analytics to support well-being oriented life. Three categories of personal data are classified from the collection of individuals’ daily life data, and a framework of well-being oriented personal data analysis is proposed, which can provide people with suggestions and advices to improve their living life.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. World Health Organization: Ecosystems and Human Well-Being: Health Synthesis, http://www.who.int/globalchange/ecosystems/ecosys.pdf Accessed 7 March 2015

  2. Gemmell, J. et al: MyLifeBits: Fulfilling the Memex Vision, Proceeding of ACM Multimedia, 235–238 (2002)

    Google Scholar 

  3. Pan, R., Matsuo, Y.: Discovery behavior patterns from social data for managing personal life. J. Jpn Soc Artifi Intel 28(6), 829–834 (2013)

    Google Scholar 

  4. Teraoka, T.: Organization and exploration of heterogeneous personal data collected in daily life. Hum Centric Comput. Inf. Sci. 2(1), 1–5 (2012)

    Google Scholar 

  5. Bentley, F. et al: Health mashups: presenting statistical patterns between wellbeing data and context in natural language to promote behavior change. ACM Trans. Comput. Hum. Interact. 20(5), 30 (2013)

    Google Scholar 

  6. Ryff, C.D., Keyes, C.L.M.: The Structure of psychological well-being revisited. J. Pers. Soc. Psychol. 69(4), 719–727 (1995)

    Article  Google Scholar 

  7. World Economic Forum: Personal data: the emergence of a new asset class, http://www3.weforum.org/docs/WEF_ITTC_PersonalDataNewAsset_Report_2011.pdf Accessed 7 March 2015

Download references

Author information

Authors and Affiliations

  1. Graduate School of Human Sciences, Waseda University, Tokyo, Japan

    Seiji Kasuya, Xiaokang Zhou, Shoji Nishimura & Qun Jin

Authors
  1. Seiji Kasuya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaokang Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shoji Nishimura
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qun Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Seiji Kasuya .

Editor information

Editors and Affiliations

  1. Seoul National University of Science and Technology, Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. National Ilan University, Yilan City, Taiwan

    Han-Chieh Chao

  3. The University of Georgia, Athens, Georgia, USA

    Hamid Arabnia

  4. The University of Aizu, Aizuwakamatsu, Japan

    Neil Y. Yen

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kasuya, S., Zhou, X., Nishimura, S., Jin, Q. (2016). A Framework of Personal Data Analytics for Well-Being Oriented Life Support. In: Park, J., Chao, HC., Arabnia, H., Yen, N. (eds) Advanced Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47895-0_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-47895-0_53

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-47894-3

  • Online ISBN: 978-3-662-47895-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation