Skip to main content
SpringerLink
Log in
Book cover

Pervasive and Mobile Sensing and Computing for Healthcare pp 1–49Cite as

Pervasive Sensing and M-Health: Vital Signs and Daily Activity Monitoring

  • Chapter

Part of the book series: Smart Sensors, Measurement and Instrumentation ((SSMI,volume 2))

Abstract

Recent advances in pervasive sensing, mobile, and pervasive computing technologies have led to deployment of new smart sensors and smart sensor networks architectures that can be worn or integrated within the living environment without affecting a person’s daily activities. These sensors promise to change vital signs and motor activity monitoring from snapshot mode to continuous monitoring mode, enabling clinicians, therapists but also accompanying persons of elderly or people with chronic diseases or disabilities to provide healthcare services based on remote continuous monitoring of the patient, pervasive health monitoring or pervasive healthcare. Using computer resources expressed by networks of servers, storage applications and Web services health monitoring and healthcare might be rapidly provisioned and released with minimal management effort or service provider interaction by using computational intelligence and Semantic Web.

A brief literature review on healthcare challenges, the deployment of unobtrusive sensors that may be used as part of pervasive sensing systems for vital signs and daily motor activity monitoring, mobile health applications and pervasive computing for pervasive health monitoring and pervasive healthcare are presented in this chapter. The chapter encompasses examples of unobtrusive sensors for health and motor activity monitoring as well as Android OS and iPhone mobile applications from Apps Store for vital and sensory function test, emergency, stress management, brain activity management, nutrition, and physical exercises. Mobile healthcare architectures developed with the contribution of the authors for vital signs and motor activity remote monitoring as well as for indoor air quality monitoring and alert on respiratory distress, which includes wearable devices (wrist worn device) and sensors integrated in objects such as walker and wheelchair are also presented in this chapter.

The presented pervasive sensing and pervasive computing approaches for health monitoring and care underscore the capabilities of this kind of systems to assure more closely coordinated forms of health and social care provision as well as personalized healthcare for better quality of life.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cutler, D.: Declining disability among the elderly. Health Affairs 20(6), 11–27 (2012)

    Article  Google Scholar 

  2. Saranummi, N., Wactlar, H.: Editorial: pervasive healthcare. Selected papers from the Pervasive Healthcare 2008 Conference, Tampere, Finland. Methods Inf Med 47(3), 175-177 (2008)

    Google Scholar 

  3. Korhonen, I., Bardram, J.E.: Guest Editorial Introduction to the Special Section on Pervasive Healthcare. IEEE Transactions on Information Technology in Biomedicine 8(3), 229–234 (2004)

    Article  Google Scholar 

  4. Kern, S.E., Jaron, D.: Healthcare technology, economics and policy: an evolving balance. IEEE Eng. Med. Biol. Mag. 22, 16–19 (2003)

    Article  Google Scholar 

  5. Economist Intelligent Unit “The future of healthcare in Europe”, The Economist, http://www.eufutureofhealthcare.com/sites/default/files/EIUJanssen%20Healthcare_Web%20version.pdf

  6. US Administration on Aging Report on Demographic Changes, http://www.aoa.dhhs.gov/aoa/stats/aging21/demography.html

  7. Population Division, DESA, United Nations. World Population Ageing 1950-2050, http://www.un.org/esa/population/publications/worldageing19502050/pdf/8chapteri.pdf

  8. United States Department of Health and Human Services. Personalized Health Care: opportunities, pathways, resources (2007), http://www.hhs.gov/myhealthcare/news/phc-report.pdf

  9. ISPOR 16th Annual International Meeting. Personalized healthcare and comparative effectiveness research: realizing the evidence on what works for whom and when (2011) http://www.ispor.org/meetings/baltimore0511/presentations/UBC_PCORI_PersonalizedHeathcareISPOR05242011.pdf

  10. IBM Global Business Services. IT- enabled personalized health care. Improving of health promotion and care delivery, http://www-935.ibm.com/services/us/gbs/bus/html/ibv-it-enabled-personalized-healthcare.html

  11. McMichael, A.: Climate change and human health, Commonwealth Health Ministers Update 2009, pp. 12–21. Pro-Book Publishing, Woodridge (2009)

    Google Scholar 

  12. Costello, A., Abbas, M., Allen, A., Ball, S., Bell, S., Bellamy, R., Friel, S., Groce, N., Johnson, A., Kett, M., Lee, M., Levy, C., Maslin, M., McCoy, D., McGuire, B., Montgomery, H., Napier, D., Pagel, C., Patel, J., de Oliveira, J.A., Redcliff, N., Rees, H., Rogger, D., Scott, J., Stephenson, J., Twigg, J., Wolff, J., Patterson, C.: Managing the health effects of climate change: Lancet and University College London Institute for Global Health Commission. Lancet 373(9676), 1693–1733 (2009)

    Article  Google Scholar 

  13. Friel, S., Butler, C., McMichael, A.: Climate change and health: Risks and Inequities. In: Benatar, S., Brock, G. (eds.) Global Health Ethics. Cambridge University Press, Cambridge (2011), http://ebooks.cambridge.org/chapter.jsf?bid=CBO9780511984792&cid=CBO9780511984792A027

    Google Scholar 

  14. Bowen, J.K., Friel, S.: Climate change adaptation: where does global health fit in the agenda? Globalization and Health 8, 10 (2012), http://www.globalizationandhealth.com/content/8/1/10

  15. Barr, D.B.: Human exposure science: a field of growing importance. J. Expo. Sci. Environ. Epidemiol. 16, 473 (2006)

    Article  Google Scholar 

  16. Stiel, I.G., Spaite, D.W., Field, B., Nesbitt, L.P., Munkley, D., Maloney, J., Dreyer, J., Toohey, L.L., Campeau, T., Dagnone, E., Lyver, M., Wels, G.A.: OPALS Study Group. Advanced life support for out-of hospital respiratory distress. New England Journal of Medicine 356, 2156–2164 (2007)

    Google Scholar 

  17. NHLBI Morbidity and Mortality Chart Book, http://www.nhlbl.nih.gov/resources/docs/cht-book.htm

  18. Manolio, T.A., Collins, F., Cox, N.J., Goldstein, B.B., Hindorff, L.A., Hunter, D.J., Mc Carthy, M.I., Ramos, E.M., Cardon, L.R., Chakravarti, A., Cho, J.H., Gutlmacher, A.E., Kong, A., Kruglyak, L., Mardis, E., Rotimi, C.N., Slatkin, M., Valle, D., Whittemorelt, A.S., Boenhnke, M., Clark, A.G., Eichler, E.E., Gibson, G., Haines, J.L., Mackay, T.F.C., McCarrol, S.A., Visscher, P.: Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009)

    Article  Google Scholar 

  19. Wild, C.P.: Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol. Biomarkers Prev. 14(8), 1847–1850 (2005)

    Article  MathSciNet  Google Scholar 

  20. Boulos, M.N.K.: Towards evidence-based, GIS-driven national spatial health information infrastructure and surveillance services in the United Kingdom. International Journal of Health Geographic (2004) http://www.ij-healthgeographics.com/

  21. Brooker, S., Kabatereine, N.B., Myatt, M., Stothard, J.R., Fenwick, A.: Rapid assessment of Schistosoma mansoni: the validity, applicability and cost-effectiveness of the Lot Quality Assurance Sampling method in Uganda. Tropical Medicine and International Health 10, 647–658 (2005)

    Article  Google Scholar 

  22. Postolache, O., Pereira, J.M., Girão, P.S., Postolache, G.: Distributed smart sensing systems for indoor monitoring of respiratory distress triggering factors. In: Mazzeo, N.A. (ed.), pp. 311–331. InTech (2011)

    Google Scholar 

  23. Postolache, O., Silva Girão, P., Sinha, M., Anand, A., Postolache, G.: Health status and air quality parameters monitoring based on mobile technology and WPAN. Int. J. Advanced Media and Communication, 139–153 (2009)

    Google Scholar 

  24. Cramp, D.G., Flowerday, A., Harrar, H., Harvey, F.E., Leicester, H.J., Roudsari, A.V.: REALITY in Home Telecare: A Systemic Approach to Evaluation. In: 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS, pp. 3927–3930 (2005)

    Google Scholar 

  25. Chana, M., Campoa, E., Estèvea, D., Fourniolsa, J.-Y.: Smart homes - current features and future perspectives, vol. 64(2), pp. 90–97. Elsevier, Maturitas (2009)

    Google Scholar 

  26. Fouquet, Y., Franco, C., Demongeot, J., Villemazet, C., Vuillerme, N.: Telemonitoring of the elderly at home: Real-time pervasive follow-up of daily routine, automatic detection of outliers and drifts. Smart Home Systems, Intech (2010)

    Google Scholar 

  27. Han, D., Kim, J., Cha, E., Lee, T.: Wheelchair type biomedical system with event-recorder function. In: Proceedings of IEEE EMBS Conference, pp. 1435–1438 (2008)

    Google Scholar 

  28. Uenoyama, T., Matsui, K., Yamada, S., Suzuki, B., Takase, M., Kawakami, M.: Non-contact respiratory monitoring system using a ceiling-attached microwave antenna. Med. Bio. Eng. Comput. 44, 835–840 (2006)

    Article  Google Scholar 

  29. Postolache, O., Girão, P., Mendes Joaquim, G., Pinheiro, E., Postolache, G.: Physiological parameters measurement based on wheelchair embedded sensors and advanced signal processing. IEEE Transaction on Instrumentation and Measurement 59(10), 2564–2574 (2010)

    Article  Google Scholar 

  30. Varshney, U.: Using wireless technologies in healthcare. Int. Journal on Mobile Communications 4(3), 354 (2006)

    Google Scholar 

  31. Doukas, C., Pliakas, T., Maglogiannis, I.: Mobile healthcare information management utilizing Cloud Computing and Android OS. In: Proceedings IEEE EMBC 2010, pp. 1037–1040 (2010)

    Google Scholar 

  32. Karlsson, J.S., Wiklund, U., Berglin, L., Östlund, M., Karlsson, M., Bäcklund, T., Lindecrantz, K., Sandsjö, L.: Wireless monitoring of heart rate and electromyographic signals using a smart T-shirt. In: Proceedings of International Workshop on Wearable Micro and Nanosystems for Personalised Health (2008), http://www.phealth2008.com/Events/papers/p7.pdf

  33. Lim, Y.G., Kim, K.-K., Park, K.: ECG recording on a bed during sleep without direct skin-contact. IEEE Transactions on Biomedical Engineering 54(4), 718–725 (2007)

    Article  Google Scholar 

  34. Ishida, S., Shiozawa, N., Fujiwara, Y., Makikawa, M.: Electrocardiogram measurement during sleep with wearing clothes using capacitively-coupled electrodes. In: Conference Proceedings IEEE Engineering in Medicine& Biology Society 2007, pp. 2647–2650 (2007)

    Google Scholar 

  35. Junnila, S., Akhbardeh, A., Värri, A., Koivistoinen, T.: An EMFi-film sensor based ballistocardiographic chair: performance and cycle extraction method. In: Proceedings of IEEE Workshop Signal Processing Systems Design and Implementation 2005, pp. 373–377 (2005)

    Google Scholar 

  36. Paajanen, M., Lekkala, J., Valimaki, H.: Electromechanical modeling and properties of the electret film EMFI. IEEE Transaction on Dielectrics and Electrical Insulation 8(4), 629–636 (2001)

    Article  Google Scholar 

  37. Postolache, O., Girão, P. S., Postolache, G., Dias Pereira, J. M.: Vital signs monitoring system based on EMFi sensors and wavelet analysis. In: Instrumentation and Measurement Technology Conference Proceedings, IMTC 2007, pp. 1–4. IEEE (2007)

    Google Scholar 

  38. Postolache, G., Maia Moura, C., Girão, P. S., Postolache, O.: Rehabilitative telehealthcare to post-stroke outcome assessment. In: Proceedings of the 5th ICST Conference in Pervasive Computing Technologies for Health Care, pp. 23–26 (2011)

    Google Scholar 

  39. Postolache, O.A., Girão, P. S., Postolache, G., Mendes Joaquim, G.: Cardio-respiratory and daily activity monitor based on FMCW Doppler radar embedded in a wheelchair. In: Conf. Proc. IEEE Engineering in Medicine and Biology Society (EMBS) 2011, pp. 1917-1921 (2011)

    Google Scholar 

  40. Kim, J., Hong, H.J., Cho, M.C., Cha, E.J., Soo, T.: Wireless biomedical signal monitoring device on wheelchair using non-contact electro-mechanical film sensor. In: Proceedings of the 29th Annual International Conference of the IEEE EMBS, pp. 574–577 (2007)

    Google Scholar 

  41. Han, D.-K., Kim, J.-M., Cha, E.-J., Lee, T.-S.: Wheelchair Type Biomedical System with Event-Recorder Function. In: roceedings of IEEE Engineering in Medicine and Biology Society (EMBS) Conference 2008, pp. 1435–1437 (2008)

    Google Scholar 

  42. Scully, C.G., Lee, J., Meyer, J., Gorbach, A.M., Granquist-Frasir, D., Mendelson, Y., Chon, K.N.: Physiological parameter monitoring from optical recording with a mobile phone. IEEE Transaction on Biomedical Engineering 59(2), 303–307 (2012)

    Article  Google Scholar 

  43. Droitcour, A., Lubecke, V.M., Lin, J., Boric-Lubecke, O.: A microwave radio for Doppler radar sensing of vital signs. In: IEEE MTTS Int. Microwave Symp. Dig., pp. 175–178 (2007)

    Google Scholar 

  44. Boric-Lubecke, O., Massagram, W., Lubecke, V.M., Host-Madsen, A.H., Jokanovic, B.: Heart rate variability assessment using Doppler radar with linear demodulation. In: Proceedings of the 38th European Microwave Conference, pp. 420–423 (2008)

    Google Scholar 

  45. Matsui, T., Arai, I., Gotoh, S., Hattori, H., Takase, B., Kikuchi, M., Ishihara, M.: A novel apparatus for non-contact measurement of heart rate variability: a system to prevent secondary exposure of medical personnel to toxic materials under biochemical hazard conditions, in monitoring sepsis or predicting multiple organ dysfunction syndrome. Biomedicine & Pharmacotherapy 59, S188–S191 (2005)

    Article  Google Scholar 

  46. Asada, H.H., Shaltis, P., Reisner, A., Sockwoo, R., Hutchinson, R.: Mobile monitoring with wearable photoplethysmographic biosensors. IEEE Engineering in Medicine and Biology Magazine 22(3), 28–40 (2003)

    Article  Google Scholar 

  47. Karkokli, R., McConville, K.M.V.: Design and development of a cost effective plantar pressure distribution analysis system for the dynamically moving feet. In: 28th Annual International Conference Engineering in Medicine and Biology Society, EMBS 2006, pp. 6008–6011 (2006)

    Google Scholar 

  48. Sugimoto, C., Tsuji, M., Lopez, G., Mosaka, H., Sasaki, K., Hirota, T., Tatsuta, S.: Development of a behavior recognition system using wireless wearable information devices. In: 1st International Symposium on Wireless Pervasive Computing 2006 (2006)

    Google Scholar 

  49. The Wyss Institute at Harvard University, http://www.bu.edu/abl/files/footwearinsight.pdf

  50. Wan, E.A., Anindya, S. P.: A tag-free solution to unobtrusive indoor tracking using wall-mounted ultrasonic transducers. In: Proceedings of IEEE IPIN (2010), http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05648178

  51. Gomes, G., Sarmento, H.: Indoor Location System using ZigBee Technology. In: Gomes, G., Sarmento, H. (eds.) Proceedings IEEE International Conference on Sensor Technologies and Applications, pp. 152–157 (2009)

    Google Scholar 

  52. Sugano, M., Kawazoe, T., Ohta, Y., Murata, M.: Indoor localization system using RSSI measurement of wireless sensor network, based on ZigBee standard. In: Proceedings IASTED Int. Conf. WSN (2006), vol. 7, pp. 54–69 (2006)

    Google Scholar 

  53. Li, B., Salter, J., Dempster, A.G., Rizos, C.: Indoor positioning techniques based on Wireless LAN. In: First IEEE Int. Conf. on Wireless Broadband & Ultra Wideband Communications (2006)

    Google Scholar 

  54. Park, Y., Lee, J., Kim, S.: Improving position estimation on RFID tag floor localization using RFID reader transmission power control. In: Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics, pp. 1716–1721 (2008)

    Google Scholar 

  55. Madeira, R., Postolache, O., Postolache, G.: Designing personalized therapeutic serious games for a pervasive assistive environment. In: 2011 IEEE 1st International Conference on Serious Games and Applications for Health (SeGAH), pp. 1–11 (2011)

    Google Scholar 

  56. Jung, K.K., Son, D.S., Eon, K.H.: RFID footwear and floor system. In: WRI World Congress on Computer Science and Information Engineering 2009, vol. 3, pp. 72–75 (2009)

    Google Scholar 

  57. Middleton, L., Buss, A.A., Bazin, A.I., Nixon, M.S.: A floor sensor system for gait recognition. In: Fourth IEEE Workshop on Automatic Identification Advanced Technologies, pp. 17–18 (2005)

    Google Scholar 

  58. Orr, R.J., Abowd, G.: The smart floor: a mechanism for natural user identification and tracking. In: Proceeding CHI EA 2000, CHI 2000, Extended Abstracts on Human Factors in Computing Systems, pp. 275–276 (2000), http://www.cc.gatech.edu/fce/pubs/floor-short.pdf

  59. Murakita, T., Ikeda, T., Ishiguro, H.: Human tracking using floor sensors based on the markov monte carlo method. In: Proc. of the 17th Int. Conf. on Pattern Recognition (ICPR), vol. 4, pp. 917–920 (2004)

    Google Scholar 

  60. Lauterbach, C., Steinhage, A., Techmer, A.: Large area wireless sensor system based on smart textile. In: Proc. of the 9th International Multiconference on Systems, Signals and Devices, SSD 2012 (2012)

    Google Scholar 

  61. Martin, E., Vinyals, O., Friedland, G., Bajcsy, R.: Precise indoor localization using smart phones. In: Proc. of the ACM International Conference on Multimedia (ACM Multimedia), pp. 787–790 (2010), http://www.icsi.berkeley.edu/pubs/speech/preciseindoor10.pdf

  62. Stone, E.E., Skubic, M.: Evaluation of an inexpensive depth camera for in-home gait assessment. Journal of ambient Intelligence ans Smart Environments 3(2), 349–361 (2011)

    Google Scholar 

  63. Pousman, Z., Stasko, J.: Ambient Information Systems: Evaluation in two paradigms. In: Pervasive 2007 Workshop: W9 Ambient Information Systems (2007), http://www.cc.gatech.edu/~john.stasko/papers/pervasive07-eval.pdf

  64. Dix, A.: Beyond intention - pushing boundaries with incidental interaction. In: Proc. Building Bridges: Interdisciplinary Context-Sensitive Computing (2002)

    Google Scholar 

  65. Shaaban, Y.A., McBurney, S., Taylor, N., Williams, M., Kalatzis, N., Roussaki, I.: User intent to support proactivity in a pervasive system. In: Proceedings of PERSIST 2009 – Workshop on Intelligent Pervasive Environment (2009), http://www.aisb.org.uk/convention/aisb09/Proceedings/PERSIST/FILES/AbuShaabanY.pdf

  66. Postolache, O., Girão, P.M.S., Postolache, G., Mendes Joaquim, G.: Dual channel smart sensor embedded in wheelchair for heart rate and autonomic nervous system monitoring. In: Biomedical Engineering, BioMed 2010 (2010), http://www.actapress.com/Content_of_Proceeding.aspx?proceedingID=629

  67. Postolache, O., Girão, P.M., Mendes Joaquim, J., Postolache, G.: Unobstrusive heart rate and respiratory rate monitor embedded on a wheelchair. In: IEEE International Workshop on Medical Measurements and Applications, MeMeA 2009, pp. 83–88 (2009)

    Google Scholar 

  68. Pinheiro, E., Postolache, O., Girão, P.M.S.: Stationary wavelet transform and principal component analysis application on capacitive electrocardiography. In: International Conference on Signals and Electronic Systems (ICSES 2010), pp. 37–40 (2010)

    Google Scholar 

  69. Postolache, O., Girão, S.P., Ribeiro, M., Carvalho, M., Catarino, A., Postolache, G.: Treat Me Well: Affective and physiological feedback for wheelchair users. In: IEEE International Symposium on Medical Measurements and Applications 2012, MeMeA 2009, pp. x–xx (2012)

    Google Scholar 

  70. Holder, C.G., Haskvitz, E.M., Weltman, A.: The effects of assistive devices on the oxygen cost, cardiovascular stress, and perception of nonweight-bearing ambulation. Journal of Orthopaedic, Sports and Physical Therapy 18(4), 537–542 (1993)

    Google Scholar 

  71. ThorMed. SpiroTube Mobile solution, http://www.thormed.com/index.php?page=products&id=spiro4

  72. Bailon, R., Sornmo, L., Laguna, P.: A robust method for ECG-based estimation of the respiratory frequency during stress testing. IEEE Transact. Biomed. Eng. 53, 1273–1285 (2006)

    Article  Google Scholar 

  73. Schäfer, A., Kratky, K.W.: Estimation of breathing rate from respiratory sinus arrhythmia: comparison of various methods. Ann. Biomed. Eng. 36(3), 476–485 (2008)

    Article  Google Scholar 

  74. Obeid, D., Sadek, S., Zaharia, G., El Zein, G.: Touch-less heartbeat detection and cardiopulmonary modeling. In: 2nd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2009, pp. 1–5 (2009)

    Google Scholar 

  75. Choi, J., Kim, D.K.: A remote compact sensor for the real-time monitoring of human heartbeat and respiration rate. IEEE Transactions on Biomedical Circuits and Systems 3(3), 181–188 (2009)

    Article  Google Scholar 

  76. Paredes, L., Madrid, P., Torruella, P., Solaeche, P., Galiana, I., Gonzalez de Santos, P.: Accurate modeling of low cost piezoresistive force sensor for haptic interface. In: Proc. IEEE International Conference on Robotics and Automatics, pp. 1828–1833 (2010)

    Google Scholar 

  77. Katulski, R.J., Namieśnik, J., Stefański, J., Sadowski, J., Wardencki, W., Szymanska, K.: Mobile monitoring system for gaseous air pollution. Metrol. Meas. Syst. XVI, 4, 677–682 (2009)

    Google Scholar 

  78. Istepanian, R., Laxminarayan, S., Pattichis, C.S. (eds.): M-Health: Emerging Mobile Health Systems. Springer (2005)

    Google Scholar 

  79. Germanakos, P., Mourlas, C., Samaras, G.: A mobile agent approach for ubiquitous and personalized eHealth information systems. In: Proceedings of the Workshop on ’Personalization for e-Health’ of the 10th International Conference on User Modeling (UM 2005), pp. 67–70 (2005)

    Google Scholar 

  80. Torgan, C.: The mHealth Summit: Local & Global Converge caroltorgan.com (2009), http://www.caroltorgan.com/mhealth-summit/

  81. Gupta, V.: Cloud Computing in Healthcare. Healthcare Express, http://www.expresshealthcare.in/201109/itathealthcare04.shtml

  82. Chetley, A., Davies, J., Trude, B., McConnell, H., Ramirez, R., Shields, T., Drury, P., Kumekawa, J., Louw, J., Fereday, G., Nyamai-Kisia, C.: Improving Health, Connecting People: the role of ICTs in the health sector in the developing countries (2006), http://www.infodev.org/en/Project.38.html

  83. World Health Organizatio. eHealth Tools & Services: Needs of The Member States (2005), http://www.who.int/kms/initiatives/tools_and_services_final.pdf

  84. Braa, K., Purkayastha, S.: Sustainable mobile information infrastructure in low resource settings. Stud. Health Technol. Inform. 157, 127–132 (2010)

    Google Scholar 

  85. The International Bank for Reconstruction and Development/The World Bank. Global Economic Prospects: Managing the next wave of globalization. World Bank report (2007) on-line at http://siteresources.worldbank.org/INTGEP2007/Resources/GEP_07_Overview.pdf

  86. International Telecommunication Union, http://www.itu.int/ITU-D/ict/index.html

  87. Mobithinking, http://mobithinking.com/mobile-marketing-tools/latest-mobile-stats

  88. Malhotra, K., Gardner, S., Rees, D.: Evaluation of GPRS Enabled Secure Remote Patient Monitoring System. In: ASMTA Conference 2005, pp. 41–48 (2005)

    Google Scholar 

  89. US Department of State. Text 4Baby, http://www.state.gov/p/eur/ci/rs/usrussiabilat/159073.htm

  90. Vital Wave Consulting. mHealth for Development: The Opportunity of Mobile Technology for Healthcare in the Developing World. United Nations Foundation, Vodafone Foundation (2009), http://www.vitalwaveconsulting.com/pdf/mHealth.pdf

  91. Forestier, E., Grace, J., Kenny, C.: Can Information and communications policy be Pro-Poor? Telecommunications Policy 26, 623–646 (2002)

    Article  Google Scholar 

  92. Lane, N.D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.T.: A survey of mobile phone sensing. IEEE Communications Magazine, 140–150 (2010)

    Google Scholar 

  93. Zhang, X., Jiang, H., Zhang, L., Zhang, C., Wang, Z., Chen, X.: An energy-efficient ASIC for wireless body sensor networks in medical applications. IEEE Transactions on Biomedical Circuits and Systems 4(1), 11–18 (2010)

    Article  Google Scholar 

  94. Yang, S.-B., Kim, Y.-G.: Power saving and delay reduction for supporting WLAN-based fixed-mobile convergence service in smartphone. IEEE Transactions on Consumer Electronics 56(4), 2747–2755 (2010)

    Article  MathSciNet  Google Scholar 

  95. Palit, R., Naik, K., Singht, A.: Impact of packet aggregation on energy consumption in smartphones. In: 7th International Wireless Communications and Mobile Computing Conference (IWCMC 2011), pp. 589–594 (2011)

    Google Scholar 

  96. Mun, M., Reddy, S., Shilton, K., Yau, N., Burke, J., Estrin, D., Hansen, M., Howard, E., West, R., Boda, P.: PIER, the personal environmental impact report, as a platform for participatory sensing systems research. In: Proc. 7th ACM MobiSys 2009, pp. 55–68 (2009)

    Google Scholar 

  97. Mooney, P., Corcoran, P.: Integrating volunteered geographic information into pervasive health computing applications. In: 5th International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health 2011), pp. 93–100 (2011)

    Google Scholar 

  98. Gurman, T.A., Rubin, S.E., Roess, A.A.: Effectiveness of mHealth behavior change communication interventions in developing countries: a systematic review of the literature. J. Health Commun. 17, 82–104 (2012)

    Article  Google Scholar 

  99. Chib, A., Wilkin, H., Ling, L.X., Hoefman, B., Van Biejma, H.: You have an important message! Evaluating the effectiveness of a text message HIV/AIDS campaign in Northwest Uganda. J. Health. Commun. 17, 146–157 (2012)

    Article  Google Scholar 

  100. Kapadia, A., Kotz, D., Triandopoulos, N.: Opportunistic Sensing: Security challenges for the new paradigm. In: Proc. 1st Communication Systems and Networks and Workshops, COMSNETS 2009, p. 10 (2009), http://www.ists.dartmouth.edu/library/437.pdf

  101. Adesina, A.O., Agbele, K.K., Februarie, R., Abidoye, A.P., Nyongesa, H.O.: Ensuring the security and privacy of information in mobile health care communication systems. South Africa Journal Science 107(9/10), 26–32 (2011)

    Google Scholar 

  102. Zittrain, J.: Ubiquitous human computing. Phil. Trans. R Soc. A 366, 3813–3821 (2008)

    Article  Google Scholar 

  103. Satyanarayanan, M.: Pervasive Computing: vision and challenges. IEEE Personal Communication (2009), http://www-rp.lip6.fr/maitrise/articles/00943998.pdf

  104. Mühleisen, H., Dentler, K.: Large-scale storage and reasoning for semantic data using swarms. IEEE Computational Intelligence Magazine 7(2), 32–44 (2012)

    Article  Google Scholar 

  105. Multi-tenant mode, http://msdn.microsoft.com/en-us/library/aa479086.aspx

  106. Er, M.J., Oentaryo, J.: Computational Intelligence. Methods and techniques [Book review]. IEEE Computational Intell. Mag. 6(4), 76–78 (2011)

    Article  Google Scholar 

  107. Medel, J., Zadeh, L., Trillas, E., Yager, R., Lawry, J., Hagras, H., Guadarramas, S.: What computing with words means to me. IEEE Comput. Intell. Mag. 5(1), 20–26 (2010)

    Article  Google Scholar 

  108. Coello, C.A.: Evolutionary multi-objective optimization: A historical view of the field. IEEE Cumput. Intell. Mag. 1(1), 28–36 (2006)

    Article  Google Scholar 

  109. Haykin, S.: Neural Networks: A Comprehensive Foundation. Prentice-Hall, Englewood Cliffs (1998)

    Google Scholar 

  110. Collins, A.M., Quillian, M.R.: Retrieval time for semantic memory. J. Verbal Learn, Verbal Behav. 8(2), 240–247 (1960)

    Article  Google Scholar 

  111. Berners-Lee, T., Hendler, J., Lassila, O.: The semantic Web. Scientific American (2001), http://www.sciam.com/print_version.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21 (2010)

  112. Chen, H., Wu, Z., Cudré-Maroux, P.: Semantic Web meets computational inteligence: state of the art and perspectives. IEEE Computational Intelligence Magazine 7(2), 67–74 (2012)

    Article  Google Scholar 

  113. Fischett, M.: The Web turns 20: linked data gives people power – Part 1 of 4. Scientific American (2010)

    Google Scholar 

  114. World Wide Web Consortium (W3C). W3C semantic web activity, http://www.w3.org/2001/sw/

  115. Berners-Lee, T.: Linked data web architecture note, http://www.w3.org/DesignIssues/LinkedData.html

  116. Prehofer, C., Bettstetter, C.: Self-organization in communication networks. Principles and design paradigms. IEEE Commun. Mag. 43(7), 78–85 (2005)

    Article  Google Scholar 

  117. Guéret, C., Schlobach, S., Dentler, K., Schut, M., Eiben, G.: Evolutionary and swarm computing for semantic Web. IEEE Computational Intelligence Magazine 7(2), 16–31 (2012)

    Article  Google Scholar 

  118. Mühleisen, H., Dentler, K.: Large-scale storage and reasoning for semantic data using swarms. IEEE Computational Intelligence Magazine 7(2), 32–44 (2012)

    Article  Google Scholar 

  119. Pan, J.Z., Thomas, E., Ren, Y., Taylor, S.: Exploiting tractable fuzzy and crisp reasoning in ontology applications. IEEE Computational Intelligence Magazine 7(2), 45–53 (2012)

    Article  Google Scholar 

  120. Liu, C., Qi, G., Wang, H., Yu, Y.: Reasoning with large scale ontologies in fuzzy pD* Using MapReduce. IEEE Computational Intelligence Magazine 7(2), 54–66 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. ISCTE-IUL, IT-IUL, Lisbon, Portugal

    Octavian Postolache

  2. IT-IST/DEEC-IST, Lisbon, Portugal

    Octavian Postolache & Pedro Silva Girão

  3. Institute for Scientific and Technological Research, Universidade Atlântica, Oeiras, Portugal

    Gabriela Postolache

  4. Instituto de Medicina Molecular, Lisbon, Portugal

    Gabriela Postolache

Authors
  1. Octavian Postolache
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pedro Silva Girão
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gabriela Postolache
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Octavian Postolache .

Editor information

Editors and Affiliations

  1. School of Engineering and Advanced Techn, AgHort Bldg A, Rm 3.77, Massey University (Manawatu Campus), Manawatu Campus, Palmerston North, 4410, New Zealand

    Subhas Chandra Mukhopadhyay

  2. ISCTE – Lisbon University Institute, School of Technology and Architecture (I, Institute of Telecommunications, Polo de Lisboa, Av. Rovisco Pais, Lisbon, 1049-001, Portugal

    Octavian A. Postolache

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Postolache, O., Girão, P.S., Postolache, G. (2013). Pervasive Sensing and M-Health: Vital Signs and Daily Activity Monitoring. In: Mukhopadhyay, S., Postolache, O. (eds) Pervasive and Mobile Sensing and Computing for Healthcare. Smart Sensors, Measurement and Instrumentation, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32538-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-32538-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32537-3

  • Online ISBN: 978-3-642-32538-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation