A Study on the Quality of Life Improvement in Fixed IoT Environments: Utilizing Active Aging Biomarkers and Big Data

Eul Hee Roh, Sang Chan Park


Purpose: Aim of this study is to suggest a framework that can measure and assess Quality of Life (QoL) of elderly people objectively, by measuring their active aging status through biomarker sensors under a Fixed Internet of Things (IoT) and Building Information Modeling (BIM) technology environment.

Methodology/Approach: An objective QoL measurement & assessment framework that can replace previous subjective QoL measurements.

Findings: In this study, we mapped and suggested the active aging measures and corresponding biomarker sensors to derive an objective Healthcare Related Quality of Life (HRQOL) composite index so that we can replace HRQOL subjective question value. We also configured an environment to objectively measure, transfer, and store biomarker sensor values using Fixed IoT and BIM.

Research Limitation/implication: We conducted a preliminary study on establishing the relationship between the existing HRQOL survey and active-aging biomarker measurements. Moreover, the research subjects were limited to being individual elderly residents of a nursing home.

Originality/Value of paper: This study is meaningful in that it suggests a method of replacing the conventional QoL survey with objective QoL measurements through IoT sensors. Furthermore, we consider the surrounding living environment that might greatly affect the QoL of individuals.


QoL; active aging; biomarker; fixed IoT; BIM

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Belsky, D.W., Caspi, A., Houts, R., Cohena, H.J., Corcorane, D.L., Danese, A., Harrington, H., Israel, S., Levine, M.E., Schaefer, J.D., Sugden, K., Williams, B., Yashin, A.I., Poulton, R. and Moffitt, T.E., 2015. Quantification of biological aging in young adults. Proceedings of the National Academy of Sciences of the United States of America, 112(30), pp.4104-4110.

Bilotta, C., Bowling, A., Casè, A., Nicolini, P., Mauri, S., Castelli, M. and Vergani, C., 2010. Dimensions and correlates of quality of life according to frailty status: a cross-sectional study on community-dwelling older adults referred to an outpatient geriatric service in Italy. Health and Quality of Life Outcomes, 8, pp.56-66.

CDC (Centers for Disease Control and Prevention), 2000. Measuring Healthy Days: Population Assessment of Health-Related Quality of Life. Georgia: Centers for Disease Control and Prevention.

Choo, S.Y., 2010. IFC & IFC-based Technology. Review of Architecture and Building Science, 54(1), pp.26-30.

Conrad, I., Matschinger, H., Riedel-Heller, S., Von Gottberg, C. and Kilian, R., 2014. The psychometric properties of the German version of the WHOQOL-OLD in the German population aged 60 and older. Health and Quality of Life Outcomes, 12(1), pp.105-117.

Kim, D. and Kim, S., 2014. A Symbiotic Design Process of Digital – Analog Models and the Role of BIM in the Next Generation Design Environment. Journal of the Architectural Institute of Korea Planning & Design, 30(11), pp.49-56.

Kim, H., Lee, C., Jung, H., Lee, G. and Kim, D., 2015. The effect of the multi intervention program applying to dementia elderly. The Journal of Korean Society of Community Based Occupational Therapy, 5(2), pp.11-21.

Kim, H. and Shim, M., 2015. The Effects of Mental Health on the Quality of Life after Stroke. Journal of Digital Convergence, 13(2), pp.237-244.

Konstantinidis, E.I., Bamparopoulos, G., Billis, A. and Bamidis, P.D., 2015. Internet of Things For an Age-Friendly Healthcare. Studies In Health Technology And Informatics, 210, pp.587-591.

Kwen, Y., 2008. A Study on Construction and Application of Evaluation Indicators in Quality of Life. Daegu University.

Lee, H. and Lee, D., 2013. Effects of a Cognition Activation Program for the Institutionalized Old-Old in Korea. Journal of Korean community nursing, 24(4), pp.427-437.

Mei, Y., 2010. Efficient scalable schemes for monitoring a large number of data streams. Biometrika, 97(2), pp.419-433.

Quantified Health, 2015. What is your biological age?. [online] Available at: < http://quantifiedhealth.blogspot.sk/2015/08/what-is-your-biological-age.html >.

Tartakovsky, A.G., Rozovskii, B.L., Blažek, R.B. and Kim, H., 2006. Detection of intrusions in information systems by sequential change-point methods. Statistical Methodology, 3(3), pp.252-340.

WHO, 2002. Active Ageing: A Policy Framework. [online] WHO. Available at: < http://www.who.int/ageing/publications/active_ageing/en/ > [Accessed May 2015].

WHO, 1998. The World Health Organization Quality of Life assessment (WHOQOL): Development and general psychometric qualities. Social Science and Medicine, 46(12), pp.1569-1585.

Wolak-Thierry, A., Novella, J.L., Barbe, C., Morrone, I., Mahmoudi, R. and Jolly, D., 2015. Comparison of QoL-AD and DQoL in elderly with Alzheimer's disease. Aging and Mental Health, 19(3), pp.274-278.

Yang, C., Selassie, A.W., Carter, R.E. and Tilley, B.C., 2012. Measuring QoL with SF-36 in Older Americans with TBI. Applied Research in Quality of Life. 7(1), pp.63-81.

Zhang, J., Seet, B. and Lie, T., 2015. Building Information Modeling for Smart Built Environments. Buildings, 5(1), pp.100-115.

DOI: http://dx.doi.org/10.12776/qip.v21i2.883


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