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Quality Analysis of Sensors Data for Personal Health Records on Mobile Devices

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Pervasive Health Knowledge Management

Part of the book series: Healthcare Delivery in the Information Age ((Healthcare Delivery Inform. Age))

Abstract

Data collected by multiple physiological sensors are being increasingly used for wellness monitoring or disease management, within a pervasiveness context facilitated by the massive use of mobile devices. These abundant complementary raw data are challenging to understand and process, because of their voluminous and heterogeneous nature, as well as the data quality issues that could impede their utilization. This chapter examines the main data quality questions concerning six frequently used physiological sensors—glucometer, scale, blood pressure meter, heart rate meter, pedometer, and thermometer—as well as patient observations that may be associated to a given set of measurements. We discuss specific details that are either overlooked in the literature or avoided by data exploration and information extraction algorithms, but have significant importance to properly preprocess these data. Making use of different types of formalized knowledge, according to the characteristics of physiological measurement devices, relevant data handled by a Personal Health Record on a mobile device, are evaluated from a data quality perspective, considering data deficiencies factors, consequences, and reasons. We propose a general scheme for sensors data quality characterization adapted to a pervasive scenario.

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References

  • Anliker, U., Ward, J. A., Lukowicz, P., Troster, G., Dolveck, F., Baer, M., Keita, F., Schenker, E. B., Catarsi, F., Coluccini, L., Belardinelli, A., Shklarski, D., Alon, M., Hirt, E., Scmid, R., & Vuskovic, M. (2004). AMON: A wearable multiparameter medical monitoring and alert system. IEEE Transactions on Information Technology in Biomedicine, 8(4), 415–427.

    Article  PubMed  Google Scholar 

  • Asada, H. H., Shaltis, P., Reisner, A., Rhee, S., & Hutchinson, R. C. (2003). Mobile monitoring with wearable photoplethysmographic biosensors. IEEE Engineering in Medicine and Biology Magazine, 22(3), 28–40.

    Article  PubMed  Google Scholar 

  • Bravata, D. M., Smith-Spangler, C., Sundaram, V., Gienger, A. L., Lin, N., Lewis, R., Stave, C. D., Olkin, I., & Sirard, J. R. (2007). Using pedometers to increase physical activity and improve health. A systematic review. Journal of the American Medical Association, 298(19), 2296–2304.

    Article  PubMed  CAS  Google Scholar 

  • Cho, J. H., Lee, H. C., Lim, D. J., Kwon, H. S., & Yoon, K. H. (2009). Mobile communication using a mobile phone with a glucometer for glucose control in Type 2 patients with diabetes: As effective as an Internet-based glucose monitoring system. Journal of Telemedicine and Telecare, 15(2), 77–82.

    Article  PubMed  Google Scholar 

  • Civan, A., Skeels, M. M., Stolyar, A., & Pratt, W. (2006). Personal health information management: Consumers’ perspectives. Proceedings of the Annual Symposium of the American Medical Informatics Association, 156–160.

    Google Scholar 

  • Coughlin, J. F., & Pope, J. (2008). Innovations in health, wellness, and aging-in-place. IEEE Engineering in Medicine and Biology Magazine, 27(4), 47–52.

    Article  Google Scholar 

  • Crawford, D. C., Hicks, B., & Thompson, M. J. (2011). Which thermometer? Factors influencing best choice for intermittent clinical temperature assessment. Journal of Medical Engineering and Technology, 30(4), 199–211.

    Google Scholar 

  • Eysenbach, G. (2008). Medicine 2.0: Social networking, collaboration, participation, apomediation, and openness. Journal of Medical Internet Research, 10(3), e22.

    Article  PubMed  Google Scholar 

  • Fortuna, E. L., Carney, M. M., Macy, M., Stanley, R. M., Younger, J. G., & Bradin, S. A. (2010). Accuracy of non-contact infrared thermometry versus rectal thermometry in young children evaluated in the emergency department for fever. Journal of Emergency Nursing, 36(2), 101–104.

    Article  PubMed  Google Scholar 

  • Gatzoulis, L., & Iakovidis, I. (2007). Wearable and portable ehealth systems. IEEE Engineering in Medicine and Biology Magazine, 26(5), 51–56.

    Article  PubMed  Google Scholar 

  • Halamka, J. D., Mandl, K. D., & Tang, P. C. (2008). Early experiences with personal health records. Journal of the American Medical Informatics Association, 15(1), 1–7.

    Article  PubMed  Google Scholar 

  • Hodge, V., & Austin, J. (2004). A survey of outlier detection methodologies. Artificial Intelligence Review, 22(2), 85–126.

    Article  Google Scholar 

  • Hung, K., Zhang, Y. T., & Tai, B. (2004). Wearable medical devices for tele-home healthcare. EMBC 04. Proceedings of the 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004 Sep 1–5, San Francisco, California, 5384–5387.

    Google Scholar 

  • ISO 15197. (2003). In vitro diagnostic test systems–requirements for blood-glucose monitoring systems for self-testing in managing diabetes mellitus. Geneva: International Organization for Standardization.

    Google Scholar 

  • Kaelber, D. C., Jha, A. K., Johnston, D., Middleton, B., & Bates, D. W. (2008). A research agenda for personal health records (PHRs). Journal of the American Medical Informatics Association, 15(6), 729–736.

    Article  PubMed  Google Scholar 

  • Korhonen, I., Pärkä, J., & Van Gils, M. (2003). Health monitoring in the home of the future. IEEE Engineering in Medicine and Biology Magazine, 22(3), 66–73.

    Article  PubMed  Google Scholar 

  • Krouwer, J., & Cembrowski, G. (2010). A review of standards and statistics used to describe blood glucose monitor performance. Journal of Diabetes Science and Technology, 4(1), 75–83.

    PubMed  Google Scholar 

  • Laakko, T., Leppanen, J., Lähteenmaki, J., & Nummiaho, A. (2008). Multipurpose mobile platform for telemedicine applications. Proceedings 2nd International Conference on Pervasive Computing Technologies for Healthcare, Tampere, Finland, 245–248.

    Google Scholar 

  • Lähteenmäki, J., Leppänen, J., Orsama, A. L., Salaspuro, V., Pirinen, J., Sormunen, M., Kaijanranta, H., & Ermes, M. (2011). Remote patient monitoring system with decision support. BIOMED 11. Proceedings of the 8th IASTED Conference on Biomedical Engineering, 2011 Feb 16–18, Innsbruck, Austria. (in press).

    Google Scholar 

  • Leijdekkers, P., & Gay, V. (2006). Personal heart monitoring system using smart phones to detect life threatening arrhythmias. CBMS 06. Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems, Salt Lake City, Utah, 157–164.

    Google Scholar 

  • Logan, A. G., McIsaac, W. J., Tisler, A., Irvine, M. J., Saunders, A., Dunai, A., Rizo, C. A., Feig, D. S., Hamill, M., Trudel, M., & Cafazzo, J. A. (2007). Mobile phone-based remote patient monitoring system for management of hypertension in diabetic patients. American Journal of Hypertension, 20(9), 942–948.

    Article  PubMed  Google Scholar 

  • Mattila, E., Korhonen, I., Salminen, J. H., Ahtinen, A., Koskinen, E., Sarela, A., Parkka, J., & Lappalainen, R. (2010). Empowering citizens for well-being and chronic disease management with wellness diary. IEEE Transactions on Information Technology in Biomedicine, 14(2), 456–463.

    Article  PubMed  Google Scholar 

  • Mundt, C. W., Montgomery, K. N., Udoh, U. E., Barker, V. N., Thonier, G. C., Tellier, A. M., Ricks, R. D., Darling, R. B., Cagle, Y. D., Cabrol, N. A., Ruoss, S. J., Swain, J. L., Hines, J. W., & Kovacs, G. T. A. (2005). A multiparameter wearable physiological monitoring system for space and terrestrial applications. IEEE Transactions on Information Technology in Biomedicine, 9(3), 382–391.

    Article  PubMed  Google Scholar 

  • Paes, B. F., Vermeulen, K., Brohet, R. M., Ploeg, T. van der, & Winter, J. P. de. (2010). Accuracy of tympanic and infrared skin thermometers in children. Archives of Disease in Childhood, 95(12), 974–978.

    Article  PubMed  CAS  Google Scholar 

  • Pagels, P., Boldemann, C., & Raustorp, A. (2011). Comparison of pedometer and accelerometer measures of physical activity during preschool time on 3- to 5-year-old children. Acta Paediatrica, 100(1), 116–120.

    Article  PubMed  Google Scholar 

  • Pagliari, C., Detmer, D., & Singleton, P. (2007). Potential of electronic personal health records. British Medical Journal, 335, 3330–3333.

    Article  Google Scholar 

  • Pantelopoulos, A., & Bourbakis, N. G. (2010). A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 40(1), 1–12.

    Article  Google Scholar 

  • Pedrolli, C., Cereda, E., & Costa, A. (2009). Fighting hospital malnutrition: Let’s start by calibrating hospital scales! Mediterranean Journal of Nutrition and Metabolism, 2, 145–147.

    Article  Google Scholar 

  • Puentes, J., & Lähteenmäki, J. (2011). Towards knowledge-based integration of personal health record data from sensors and patient observations. HealthInf 11. Proceedings 4th International Conference on Health Informatics, 2011 Jan 26–29, Rome, Italy, 280–285.

    Google Scholar 

  • Sacks, D. B., Bernhardt, P., Dunka, L. J., Goldstein, D. E., Hortin, G. L., & Mueller, P. (2002). Point-of-care blood glucose testing in acute and chronic care facilities; Approved Guideline (2nd ed.). C30-A2, 22(17).

    Google Scholar 

  • Salvi, P., Lio, G., Labat, C., Ricci, E., Pannier, B., & Benetos, A. (2004). Validation of a new non-invasive portable tonometer for determining arterial pressure wave and pulse wave velocity: The PulsePen device. Journal of Hypertension, 22(12), 2285–2293.

    Article  PubMed  CAS  Google Scholar 

  • Schneider, P. L., Crouter, S. E., Lukajic, O., & Basset, D. R. (2003). Accuracy and reliability of 10 pedometers for measuring steps over a 400-m walk. Medicine & Science in Sports & Exercise, 35(10), 1779–1784.

    Article  Google Scholar 

  • Schneider, P. L., Crouter, S. E., & Basset, D. R. (2004). Pedometer measures of free-living physical activity: Comparison of 13 models. Medicine & Science in Sports & Exercise, 36(2), 331–335.

    Article  Google Scholar 

  • Sessler, D. I. (2008). Temperature monitoring and perioperative thermoregulation. Anesthesiology, 109(2), 318–338.

    Article  PubMed  Google Scholar 

  • Silva, J. M., Mouttham, A., & El Saddik, A. (2009). UbiMeds: A mobile application to improve accessibility and support medication adherence. Proceedings of the 1st ACM SIGMM International Workshop on Media Studies and Implementations that Help Improving Access to Disabled Users, 71–78.

    Google Scholar 

  • Sriram, J., Shin, M., Kotz, D., Rajan, A., Sastry, M., & YarvisInt, M. (2009). Challenges in data quality assurance in pervasive health monitoring systems. Proceedings of Future of Trust in Computing, 129–142.

    Google Scholar 

  • Stead, W. W., & Lin, H. S. (2009). Computational technology for effective health care: Immediate steps and strategic directions. National Research Council of the national Academies. Washington, DC: National Academies Press.

    Google Scholar 

  • Steele, B. G., Belza, B., Cain, K., Warms, C., Coppersmith, J., & Howard, J. (2003). Bodies in motion: Monitoring daily activity and exercise with motion sensors in people with chronic pulmonary disease. Journal of Rehabilitation Research & Development, 40(5), 45–58.

    Article  Google Scholar 

  • Strömgren, A. S., Groenvold, M., Pedersen, L., Olsen, A. K., Spile, M., & Sjøgren, P. (2001). Does the medical record cover the symptoms experienced by cancer patients receiving palliative care? A comparison of the record and patient self-rating. Journal of Pain and Symptom Management, 21(3), 189–196.

    Article  PubMed  Google Scholar 

  • Strycker, L. A., Duncan, S. C., Chaumeton, N. R., Duncan, T. E., & Toobert, D. J. (2007). Reliability of pedometer data in samples of youth and older women. International Journal of Behavioral Nutrition and Physical Activity, 4, 4.

    Article  PubMed  Google Scholar 

  • Tang, P. C., Ash, J. S., Bates, D. W., Overhage, J. M., & Sands, D. Z. (2006). Personal health records: Definitions, benefits, and strategies for overcoming barriers to adoption. Journal of the American Medical Informatics Association, 13(2), 121–126.

    Article  PubMed  CAS  Google Scholar 

  • Tatara, N., Arsand, E., Nilsen, H., & Hartvigsen, G. (2009). A review of mobile terminal-based applications for self-management of patients with diabetes. eTELEMED 09. Proceedings of the International Conference on eHealth, Telemedicine, and Social Medicine, 166–175.

    Google Scholar 

  • Taylor, A. W., Grande, E. D., Gill, T. K., Chittleborough, C. R., Wilson, D. H., Adams, R. J., Grant, J. F., Phillips, P., Appleton, S., & Ruffin, R. E. (2006). How valid are self-reported height and weight? A comparison between CATI self-report and clinic measurements using a large cohort study. Australian and New Zealand Journal of Public Health, 30(3), 238–246.

    Article  PubMed  Google Scholar 

  • Tudor-Locke, C., & Bassett, D. R. (2004). How many steps/day are enough? Preliminary pedometer indices for public health. Sports Medicine, 34(1), 1–8.

    Article  PubMed  Google Scholar 

  • Tudor-Locke, C., Bassett, D. R., Swartz, A. M., Strath, S. J., Parr, B. B., Reis, J. P., Dubose, K. D., & Ainsworth, B. E. (2004). A preliminary study of one year of pedometer self monitoring. Annals of Behavioral Medicine, 28(3), 158–162.

    Article  PubMed  Google Scholar 

  • Walters, D. L., Sarela, A., Fairfull, A., Neighbour, K., Cowen, C., Stephens, B., Sellwood, T., Sellwood, B., Steer, M., Aust, M., Francis, R., Lee, C. K., Hoffman, S., Brealey, G., & Karunanithi, M. (2010). A mobile phone-based care model for outpatient cardiac rehabilitation: The care assessment platform (CAP). BMC Cardiovascular Disorders, 10, 5.

    Article  PubMed  Google Scholar 

  • Wheatley, I. (2006). The nursing practice of taking level 1 patient observations. Intensive and Critical Care Nursing, 22(2), 115–121.

    Article  PubMed  Google Scholar 

  • Worringham, C., Rojek, A., & Stewart, I. (2011). Development and feasibility of a Smartphone, ECG and GPS based system for remotely monitoring exercise in cardiac rehabilitation. PLoS One, 6(2), e14669.

    Article  CAS  Google Scholar 

  • Yon, B., Johnson, R., Harvey-Berino, J., Gold, B., & Howard, A. (2007). Personal digital assistants are comparable to traditional diaries for dietary self-monitoring during a weight loss program. Journal of Behavioral Medicine, 30(2), 165–175.

    Article  PubMed  Google Scholar 

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Acknowledgment

This work was supported in part by Telecom Bretagne and in part by VTT and the Finnish Funding Agency for Technology and Innovation (Tekes) in the framework of the ITEA2/Care4Me project.

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Authors and Affiliations

  1. Institut Telecom, Département Images et Traitement de l’Information, Telecom Bretagne, Technopôle Brest-Iroise, CS 83818, 29238, Brest Cedex 3, France

    John Puentes, Julien Montagner & Laurent Lecornu

  2. Knowledge Intensive Services, VTT Technical Research Center of Finland, Otaniemi, Finland

    Jaakko Lähteenmäki

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  1. John Puentes
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  2. Julien Montagner
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  3. Laurent Lecornu
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  4. Jaakko Lähteenmäki
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Correspondence to John Puentes .

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Editors and Affiliations

  1. , Coventry University, Health Design and Technology Institute (, Puma Way, COVENTRY West Midlands, CV1 2TT, United Kingdom

    Rajeev Bali

  2. The University of Adelaide Business Scho, Pulteney Street 10, Adelaide, 5005, South Australia, Australia

    Indrit Troshani

  3. Glen Crescent 131, Thornhill, L4J 4W4, Ontario, Canada

    Steve Goldberg

  4. , RMIT University, School of Business Information Technolog, GPO Box 2476, Melbourne VIC, 3001, Australia

    Nilmini Wickramasinghe

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Puentes, J., Montagner, J., Lecornu, L., Lähteenmäki, J. (2013). Quality Analysis of Sensors Data for Personal Health Records on Mobile Devices. In: Bali, R., Troshani, I., Goldberg, S., Wickramasinghe, N. (eds) Pervasive Health Knowledge Management. Healthcare Delivery in the Information Age. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4514-2_10

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  • DOI: https://doi.org/10.1007/978-1-4614-4514-2_10

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  • Online ISBN: 978-1-4614-4514-2

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