Skip to main content
Springer Nature Link
Log in

A Fuzzy Human Model for Blood Pressure Estimation

  • Conference paper
Advanced Intelligent Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 268))

  • 810 Accesses

Abstract

The paper describes a blood pressure prediction model. The model predicts blood pressure of the subject based on trend of the blood pressure, body weight and number of steps. To predict it, we make autoregressive (AR) model, liner prediction model, body weight based prediction model and steps based prediction model. These models are boosted by fuzzy logic. The fuzzy degrees are calculated from mean absolute prediction error, correlation coefficient and variation amount for the learning data. In our experiment, we collected blood pressure, body weight and number of steps of 453 subjects from WellnessLINK which is an internet life-log service. Our proposed model predicted their blood pressures. The mean correlation coefficient between the predicted values and measurement systolic blood pressures was 0.895.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Ministry of Health, Labour and Welfare, http://www.mhlw.go.jp/index.shtml

  2. Japan Preventive Association of Life-style related Disease, http://www.seikatsusyukanbyo.com/

  3. Nakajima, H., Hasegawa, Y., Tasaki, H., Iwami, T., Tsuchiya, N.: Health Manegement Technology as a General Solution Framework. SICE Journal of Control, Measurement, and System Integration, vol 1, 257–264 (2008)

    Article  Google Scholar 

  4. Nakajima, H., Shiga, T., Hata, Y.: System Health Care - Health Management Technology. In: Proc. of IEEE 43rd Int. Symp. on Multiple-Valued Logic, pp. 6–11 (2013)

    Google Scholar 

  5. Tanii, H., Nakajima, H., Tsuchiya, N., Kuramoto, K., Kobashi, S., Hata, Y.: A Fuzzy Time-Series Prediction Model with Multi-biological Data for Health Management. In: Proc. of the 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligent Systems, pp. 1265–1268 (2012)

    Google Scholar 

  6. Tanii, H., Nakajima, H., Tsuchiya, N., Kuramoto, K., Kobashi, S., Hata, Y.: A Fuzzy-AR Model to Predict Human Body Weights. In: Proc. of 2012 IEEE World Congress on Computational Intelligence, pp. 2027–2032 (2012)

    Google Scholar 

  7. Tamura, T., Mizukawa, I., Sekine, M., Kimura, Y.: Monitoring and Evaluation of Blood Pressure Changes with a Home Healthcare System. IEEE Trans. on Information Technology in Biomedical 15(4), 602–607 (2011)

    Article  Google Scholar 

  8. Moreau, K.L., Degarmo, R., Langley, J., McMahon, C., Howley, E.T., Bassett, D.R., Thompson, D.L.: Increasing Daily Walking Lowers Blood Pressure in Postmenopausal Women. Med. Sci. Sports Exerc. 33(11), 1825–1831 (2001)

    Article  Google Scholar 

  9. Iwane, M., Arita, M., Tomimoto, S., Satani, O., Matsumoto, M., Miyashita, K., Nishio, I.: Walking 10000 Steps/Day or More Reduces Blood Pressureand Sympathetic Nerve Activity in Mild Essential Hypertension. Hypertens. Res. 23(6), 573–580 (2000)

    Article  Google Scholar 

  10. Brennan, P.J., Greenberg, G., Miall, W.E., Thompson, S.G.: Seasonal Variation in Arterial Blood Pressure. British Medical Journal 285(6346), 919–923 (1982)

    Article  Google Scholar 

  11. Alperovitch, A., Lacombe, L.M., Hanon, O., Dartigues, J.F., Ritchie, K., Ducimetiera, P., Tzourio, C.: Relationship Between Blood Pressure and Outdoor Temperature in a Large Sample of Elderly Individuals. Archives of Internal Medicine 169(1), 75–80 (2009)

    Article  Google Scholar 

  12. Wellness LINK, Omron Healthcare, http://www.wellnesslink.jp/p/index.html

  13. Wang, J., Zhang, T.: Degradation Prediction Method by Use of Autoregressive Algorithm. In: Proc. of IEEE Int. Conf. on Industrial Technology 2008, pp. 1–6 (2008)

    Google Scholar 

  14. Gersch, W., Brotherton, T.: AR Model Prediction of Time Series with Trends and Seasonalities: A contrast With Box-Jenkins Modeling. In: Decision and Control including the Symposium on Adaptive Processes, vol. 19, p. 988 (1980)

    Google Scholar 

  15. Akaike, H.: A New Look at The Statistical Model Identification. IEEE Transactions 19, 716–723 (1974)

    MATH  MathSciNet  Google Scholar 

  16. Shibata, R.: Selection of the order of an autoregressive model by Akaike’s information criterion. Biometrika 63, 117–126 (1975)

    Article  Google Scholar 

  17. Zadeh, L.A.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  18. Zadeh, L.A.: The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets and Sysems 11(1-3), 199–227 (1983)

    Article  MATH  MathSciNet  Google Scholar 

  19. Kruse, R., Gebhardt, J., Kalawonn, F.: Foundations of fuzzy systems, 1st edn. John Wiley & Sons Ltd. (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School of Engineering, University of Hyogo, 2167, Shosha, Himeji, Hyogo, 671-2280, Japan

    Takahiro Takeda & Yutaka Hata

  2. Technology and Intellectual Property H.Q., OMRON Corporation, Kizugawa, Japan

    Hiroshi Nakajima & Naoki Tsuchiya

  3. WPI Immunology Frontier Research Center, Osaka University, Osaka, Japan

    Yutaka Hata

Authors
  1. Takahiro Takeda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hiroshi Nakajima
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Naoki Tsuchiya
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yutaka Hata
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Takahiro Takeda .

Editor information

Editors and Affiliations

  1. Daejeon University, Daejeon, Korea, Republic of (South Korea)

    Yong Soo Kim

  2. Mokpo National University, Jeonnam, Korea, Republic of (South Korea)

    Young J. Ryoo

  3. Seokyung University, Seoul, Korea, Republic of (South Korea)

    Moon-soo Jang

  4. Chonnam National University, Gwangju, Korea, Republic of (South Korea)

    Young-Chul Bae

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Takeda, T., Nakajima, H., Tsuchiya, N., Hata, Y. (2014). A Fuzzy Human Model for Blood Pressure Estimation. In: Kim, Y., Ryoo, Y., Jang, Ms., Bae, YC. (eds) Advanced Intelligent Systems. Advances in Intelligent Systems and Computing, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-319-05500-8_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-05500-8_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05499-5

  • Online ISBN: 978-3-319-05500-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics