Tracking of Monthly Health Condition Change from Daily Measurement of Systolic Blood Pressure

Wenxi Chen, Toshiyo Tamura

Abstract

This paper presents an approach to detect monthly biorhythmic change using daily measurement of systolic blood pressure (SBP) at home. As a part of health promotion campaign initiated in 1994, more than 600 households in West Aizu village of northern Japan were provided devices for daily measurement of blood pressure, electrocardiogram, body temperature and body weight. This paper demonstrates an outcome of data analysis of daily SBP collected in two years from an elder couple at age of seventies. The personal reference profile is gained by averaging individual monthly profiles over 24 months. Dynamic time warping algorithm estimates the similarity between personal reference profile and monthly SBP profile. The results show that an extraordinary deviation from usual biorhythmicity can be found in both the wife and the husband happened in July and February which respectively indicates individual health condition change confirmed by personal medical record. The results suggest that even it is difficult to identify any significant variation from the daily SBP directly, proper analysis of the raw SBP measured over a long-term period helps tracking functional information of health condition change and serving as an effective evidence for health management.

References

  1. IBM Corp., 2011. IBM big data and information management http://www-01.ibm.com/software/data/ bigdata/ Accessed Aug. 22, 2014.
  2. Zins, C., 2007. Conceptual Approaches for Defining Data, Information, and Knowledge. Journal of the American Society for Information Science and Technology; 58(4):479-493.
  3. Ginsberg, J., Mohebbi, M., Patel, R., Brammer, L., Smolinski, M., Brilliant, L., 2008. Detecting influenza epidemics using search engine query data. Nature; 457:1012-1014.
  4. West Aizu, 2003. Challenge to 100 Years of Age - The Making of a Healthy Village through a Total Care Solution, Fukushima: Zaikai21 Publishing House.
  5. Savitzky, A. & Golay, M. J. E. 1964. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Analytical Chemistry; 36(8):1627-1639.
  6. Salvador, S., Chan, P., 2007. Toward Accurate Dynamic Time Warping in Linear Time and Space. Intelligent Data Analysis; 11(5):561-580.
Download


Paper Citation


in Harvard Style

Chen W. and Tamura T. (2015). Tracking of Monthly Health Condition Change from Daily Measurement of Systolic Blood Pressure . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015) ISBN 978-989-758-068-0, pages 69-74. DOI: 10.5220/0005203400690074


in Bibtex Style

@conference{healthinf15,
author={Wenxi Chen and Toshiyo Tamura},
title={Tracking of Monthly Health Condition Change from Daily Measurement of Systolic Blood Pressure},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)},
year={2015},
pages={69-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005203400690074},
isbn={978-989-758-068-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)
TI - Tracking of Monthly Health Condition Change from Daily Measurement of Systolic Blood Pressure
SN - 978-989-758-068-0
AU - Chen W.
AU - Tamura T.
PY - 2015
SP - 69
EP - 74
DO - 10.5220/0005203400690074