A Web Application for Automatic Analysis on Life-style Factors Affecting Personal Health from Self-tracking Data - Towards User-side Statistics Free Personal Data Analysis

Zilu Liang

Abstract

The advent of commercial portable sensing devices has enabled many non-experts to collect their own data, and there has been a boom in health-centric self-monitoring and tracking. However, huge amount of these data remain unanalyzed simply because many of the data owners have no idea what to do with the large amount of data they have collected. Existing data analysis software tools were designed for statisticians or data scientists who have strong background in related fields. These tools are thus not usable for non-experts who have limited or no knowledge on statistics and programming. As more and more people start to collect their own data, it becomes important to solve the following problem: How to empower non-experts with an effective and easily usable tool to analyze their personal data? This project aims to address this problem by developing an online data analysis software tool to help non-experts gain insights from their personal data at simply few clicks, which requires no statistics background from the users. I have developed a prototype of the proposed web application. It is expected that the developed data analysis web application will not only help individuals identify the critical life-style factors that affect their health conditions and thus make it possible for them to personalize their healthcare plans for the best health outcome, but also help reduce public health cost and potential financial lost associated with poor health of the working population.

References

  1. A. McWilliam, R. Lutter, C. N. (2006). Health care savings from personalizing medicine using genetic testing: the case of warfarin. AEI-Brookings Joint Center for Regulatory Studies.
  2. Allison, P. D. (2001). Missing Data. SAGE Publications.
  3. G. L. Schlomer, S. B. and Card, N. A. (2010). Best practices for missing data management in counseling psychology. Journal of Counseling Psychology, 57(1):1-10.
  4. J. D. Tenenbaum, A. James, K. P.-N. (2012). An altered treatment plan based on direct to consumer (dtc) genetic testing: personalized medicine from the patient/pin-cushion perspective. Journal of Personalized Medicine, 2(4):192-200.
  5. J. E. Broderick, J. E. Schwartz, S. S. e. a. (2003). Signaling does not adequately improve diary compliance. Annals of Behavioral Medicine, 26:139-148.
  6. Krasner, G. E. and Pope, S. T. (1988). A cookbook for using the model-view controller user interface paradigm in smalltalk-80. Journal of Object-Oriented Programming, 1(3):26-49.
  7. P. E. McKnight, K. M. McKnight, S. S. and Figueredo, A. J. (2007). Missing data: A gentle introduction. New York: Guilford Press.
  8. S. R. Wisniewski, A. C. Leon, M. W. O. and Trivedi, M. H. (2006). Prevention of missing data in clinical research studies. Biological Psychiatry, 59:997-1000.
  9. S. Ruby, D. T. and Hansson, D. H. (2013). Agile Web Development with Rails 4. Pragmatic Bookshelf.
  10. Swan, M. (2013). The quantified self: fundamental disruption in big data science and biological discovery. Big Data, 1(2):85-99.
  11. W. N. Venables, D. M. S. and the R core Team (2014). An introduction to r (version 3.1.1).
Download


Paper Citation


in Harvard Style

Liang Z. (2015). A Web Application for Automatic Analysis on Life-style Factors Affecting Personal Health from Self-tracking Data - Towards User-side Statistics Free Personal Data Analysis . In Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015) ISBN , pages 9-13


in Bibtex Style

@conference{dcbiostec15,
author={Zilu Liang},
title={A Web Application for Automatic Analysis on Life-style Factors Affecting Personal Health from Self-tracking Data - Towards User-side Statistics Free Personal Data Analysis},
booktitle={Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015)},
year={2015},
pages={9-13},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={},
}


in EndNote Style

TY - CONF
JO - Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015)
TI - A Web Application for Automatic Analysis on Life-style Factors Affecting Personal Health from Self-tracking Data - Towards User-side Statistics Free Personal Data Analysis
SN -
AU - Liang Z.
PY - 2015
SP - 9
EP - 13
DO -