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

  • John Puentes
  • Julien Montagner
  • Laurent Lecornu
  • Jaakko Lähteenmäki
Part of the Healthcare Delivery in the Information Age book series (Healthcare Delivery Inform. Age)


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.


Knowledge for data validation Quality estimation of heterogeneous data Pervasive health monitoring Data understanding Physiological sensors Mobile devices 



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.


  1. 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.PubMedCrossRefGoogle Scholar
  2. 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.PubMedCrossRefGoogle Scholar
  3. 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.PubMedCrossRefGoogle Scholar
  4. 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.PubMedCrossRefGoogle Scholar
  5. 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
  6. 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.CrossRefGoogle Scholar
  7. 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
  8. Eysenbach, G. (2008). Medicine 2.0: Social networking, collaboration, participation, apomediation, and openness. Journal of Medical Internet Research, 10(3), e22.PubMedCrossRefGoogle Scholar
  9. 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.PubMedCrossRefGoogle Scholar
  10. Gatzoulis, L., & Iakovidis, I. (2007). Wearable and portable ehealth systems. IEEE Engineering in Medicine and Biology Magazine, 26(5), 51–56.PubMedCrossRefGoogle Scholar
  11. 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.PubMedCrossRefGoogle Scholar
  12. Hodge, V., & Austin, J. (2004). A survey of outlier detection methodologies. Artificial Intelligence Review, 22(2), 85–126.CrossRefGoogle Scholar
  13. 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
  14. 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
  15. 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.PubMedCrossRefGoogle Scholar
  16. 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.PubMedCrossRefGoogle Scholar
  17. 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.PubMedGoogle Scholar
  18. 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
  19. 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
  20. 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
  21. 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.PubMedCrossRefGoogle Scholar
  22. 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.PubMedCrossRefGoogle Scholar
  23. 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.PubMedCrossRefGoogle Scholar
  24. 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.PubMedCrossRefGoogle Scholar
  25. 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.PubMedCrossRefGoogle Scholar
  26. Pagliari, C., Detmer, D., & Singleton, P. (2007). Potential of electronic personal health records. British Medical Journal, 335, 3330–3333.CrossRefGoogle Scholar
  27. 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.CrossRefGoogle Scholar
  28. 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.CrossRefGoogle Scholar
  29. 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
  30. 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
  31. 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.PubMedCrossRefGoogle Scholar
  32. 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.CrossRefGoogle Scholar
  33. 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.CrossRefGoogle Scholar
  34. Sessler, D. I. (2008). Temperature monitoring and perioperative thermoregulation. Anesthesiology, 109(2), 318–338.PubMedCrossRefGoogle Scholar
  35. 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
  36. 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
  37. 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
  38. 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.CrossRefGoogle Scholar
  39. 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.PubMedCrossRefGoogle Scholar
  40. 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.PubMedCrossRefGoogle Scholar
  41. 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.PubMedCrossRefGoogle Scholar
  42. 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
  43. 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.PubMedCrossRefGoogle Scholar
  44. 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.PubMedCrossRefGoogle Scholar
  45. 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.PubMedCrossRefGoogle Scholar
  46. 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.PubMedCrossRefGoogle Scholar
  47. Wheatley, I. (2006). The nursing practice of taking level 1 patient observations. Intensive and Critical Care Nursing, 22(2), 115–121.PubMedCrossRefGoogle Scholar
  48. 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.CrossRefGoogle Scholar
  49. 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.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • John Puentes
    • 1
  • Julien Montagner
    • 1
  • Laurent Lecornu
    • 1
  • Jaakko Lähteenmäki
    • 2
  1. 1.Institut Telecom, Département Images et Traitement de l’InformationTelecom BretagneBrest Cedex 3France
  2. 2.Knowledge Intensive Services, VTT Technical Research Center of FinlandOtaniemiFinland

Personalised recommendations