Abstract
It is well known that environment and human health have a close relationship. Many researchers have pointed out the high association between the condition of an environment (e.g. pollutant concentrations, weather variables) and the qualification of health (e.g. cardio-respiratory, psychophysiology) [1, 10]. Meanwhile, environment information can be recorded accurately by sensors installed in stations, most of the health information comes from interviews, surveys, or records from medical organizations. The common approach for collecting and analyzing data to discover the association between environment and health outcomes is first isolating a predefined location then collecting all related data inside such a location. The size of this location can be scaled from local (e.g. city, province, country) to global (e.g. region, worldwide) scopes. Nevertheless, this approach cannot give a close-up perspective of an individual scale (i.e. the reaction of individual’s health against his/her surrounding environment during his/her lifetime). To fulfill this gap, we create the SEPHLA: the surrounding-environment personal-health lifelog archive. This purpose of creating this archive is to create a dataset at the individual scale by collecting psychophysiological (e.g. perception, heart rate), pollutant concentrations (e.g. \(PM_{2.5}\), \(NO_{2}\), \(O_{3}\)), weather variables (e.g. temperature, humidity), and urban nature (e.g. GPS, images, comments) data via wearable sensors and smart-phones/lifelog-cameras attached to each person. We explore and exploit this archive for better understanding the impact of an environment on human health at the individual level. We also address challenges of organizing, extending, and searching SEPHLA archive.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
- 4.
The Panel Study of Income Dynamic.
- 5.
- 6.
References
Prüss-Üstün, A., Corvalán, C.: Preventing disease through healthy environments - towards an estimate of the environmental burden of disease. World Health Organ. (2006). ISBN 92 4 159382 2
Nachman, K.E., Parker, J.-D.: Exposures to fine particulate air pollution and respiratory outcomes in adults using two national datasets: a cross-sectional study. J. Environ. Health 11, 25 (2012)
Beatty, T.K.-M., Shimshack, J.-P.: Air pollution and children’s respiratory health: a cohort analysis. J. Environ. Econ. Manag. 67(1), 39–57 (2014)
Carey, M., et al.: Traffic pollution and the incidence of cardiorespiratory outcomes in an adult cohort in London. J. Occup. Environ. Med. 73, 849–856 (2016)
Newell, K., Kartsonaki, C., Lam, K.B.H., Kurmi, O.: Cardiorespiratory health effects of gaseous ambient air pollution exposure in low and middle income countries: a systematic review and meta-analysis. J. Environ. Health 17(41), 1–14 (2018)
Requia, J.-W., Adams, D.-M., Arain, A., Papatheodorou, S., Koutrakis, P., Mahmoud, M.: Global association of air pollution and cardiorespiratory diseases: a systematic review, meta-analysis, and investigation of modifier variables. Syst. Rev. AJPH 108(S2), 123–130 (2018)
Bullinger, M.: Psychological effects of air pollution on healthy residents: a time-series approach. J. Environ. Psychol. 9, 103–118 (1989)
Sass, V., Kravitz-Wirtz, N., Karceski, M.-S., Hajat, A., Crowder, K., Takeuchi, D.: The effects of air pollution on individual psychological distress. J. Health Place 48, 72–79 (2017)
Ren, M., et al.: The short-term effects of air pollutants on respiratory disease mortality in Wuhan, China: comparison of time-series and case-crossover analyses. Sci. Rep. 7(40482), 1–9 (2017)
Shanahan, D.F., Fuller, R.A., Bush, R., Lin, B.B., Gaston, K.J.: The health benefits of urban nature: how much do we need? Bioscience 65(5), 476–485 (2015)
Pagani, M., et al.: Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circ. Res. 59, 178–193 (1986)
Wong, T.W., Tam, W.W.S., Yu, I.T.S., Lau, A.K.H., Pang, S.W., Wong, A.H.S.: Developing a risk-based air quality health index. Atmos. Environ. 76, 52–58 (2013)
Nishi, A., Araki, K., Saito, K., Kawabata, K., Seko, H.: The consideration and application of the quality control method for the atmospheric environmental regional observation system (AEROS) meteorological observation data. Tenki ( Bull. J. Meteorol. Soc. Jpn.) 62(8), 627–639 (2015)
Thom, E.C.: The discomfort index. Weatherwise 12, 57–60 (1959)
Dao, M.S., Pongpaichet, S., Jalali, L., Kim, K.S., Jain, R., Zettsu, K.: A real-time complex event discovery platform for cyber-physical-social system. In: ICMR 2014 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Sato, T., Dao, MS., Kuribayashi, K., Zettsu, K. (2019). SEPHLA: Challenges and Opportunities Within Environment - Personal Health Archives. In: Kompatsiaris, I., Huet, B., Mezaris, V., Gurrin, C., Cheng, WH., Vrochidis, S. (eds) MultiMedia Modeling. MMM 2019. Lecture Notes in Computer Science(), vol 11295. Springer, Cham. https://doi.org/10.1007/978-3-030-05710-7_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-05710-7_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05709-1
Online ISBN: 978-3-030-05710-7
eBook Packages: Computer ScienceComputer Science (R0)