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Future of Healthcare—Sensor Data-Driven Prognosis

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Wireless World in 2050 and Beyond: A Window into the Future!

Part of the book series: Springer Series in Wireless Technology ((SSWT))

Abstract

Connected Wellness/Healthcare is all about retrieving people’s physiological parameters through sensors and performing analysis. Individually, such analytics can help a patient to maintain a wellness regime, or to decide when to see a doctor, and can assist doctors in diagnosis. Collectively, such analytics, if performed over a long time over large set of patients, has the potential to discover new disease diagnostic and treatment protocols. In this chapter, we first discuss how advances in sensing and analytics can take us from a reactive illness-driven healthcare system to a proactive wellness-driven system. We introduce an IoT driven architecture and discuss how non-invasive, affordable, unobtrusive sensing using mobile phones, wearables and nearables is making physiological and pathological data collection from human body possible in thus far unimaginable ways. We also introduce breakthrough technologies in form of exosomes and 3D organ printing that has the potential to disrupt the future healthcare landscape.

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Notes

  1. 1.

    http://www.aoa.acl.gov/Aging_Statistics/index.aspx.

  2. 2.

    http://www.continuaalliance.org.

  3. 3.

    http://www.tcs.com/about/research/Pages/TCS-Connected-Universe-Platform.aspx.

  4. 4.

    http://www.omron-healthcare.com.

  5. 5.

    http://www.samsung.com/in/business/business-products/healthcare-product.

  6. 6.

    http://www.itu.int/en/ITU-D/Statistics/Documents/statistics/2015/ITU_Key_2005-2015_ICT_data.xls.

  7. 7.

    http://www.emarketer.com/Article/2-Billion-Consumers-Worldwide-Smartphones-by-2016/1011694.

  8. 8.

    https://www.fitbit.com.

  9. 9.

    http://www.shimmersensing.com/.

  10. 10.

    https://www.empatica.com/.

  11. 11.

    http://www.bluetooth.com/Pages/low-energy-tech-info.aspx.

  12. 12.

    http://www.healthline.com/health-news/diabetes-google-develops-glucose-monitoring-contact-lens-012314.

  13. 13.

    http://www.superiorideas.org/projects/infant-teardrop.

  14. 14.

    http://www.wired.com/2014/11/sweat-sensors/.

  15. 15.

    http://www.marsdd.com/news-and-insights/ingestibles-smart-pills-revolutionize-healthcare/.

  16. 16.

    http://www.the-scientist.com/?articles.view/articleNo/30793/title/Exosome-Explosion/.

  17. 17.

    http://apps.who.int/classifications/icd10/browse/2016/en.

  18. 18.

    https://www.nlm.nih.gov/research/umls.

  19. 19.

    https://www.nlm.nih.gov/research/umls/rxnorm.

  20. 20.

    https://en.wikipedia.org/wiki/Curse_of_dimensionality.

  21. 21.

    http://googleblog.blogspot.com/2012/06/using-large-scale-brain-simulations-for.html.

  22. 22.

    https://en.wikipedia.org/wiki/A_Game_of_Thrones.

  23. 23.

    http://awoiaf.westeros.org/index.php/Wall.

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Acknowledgments

We thank all our fellow scientists and engineers at Innovation Lab, TCS for their help, inputs and observations.

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Authors and Affiliations

  1. Innovation Labs, Tata Consultancy Services, Kolkata, India

    Arpan Pal, Arijit Mukherjee & Swarnava Dey

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  1. Arpan Pal
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  2. Arijit Mukherjee
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  3. Swarnava Dey
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Corresponding author

Correspondence to Arpan Pal .

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Editors and Affiliations

  1. Center for TeleInFrastruktur, Aalborg University, Aalborg, Denmark

    Ramjee Prasad

  2. Skydoot, Inc, Woodside, California, USA

    Sudhir Dixit

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Pal, A., Mukherjee, A., Dey, S. (2016). Future of Healthcare—Sensor Data-Driven Prognosis. In: Prasad, R., Dixit, S. (eds) Wireless World in 2050 and Beyond: A Window into the Future!. Springer Series in Wireless Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-42141-4_9

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  • DOI: https://doi.org/10.1007/978-3-319-42141-4_9

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