Skip to main content
Springer Nature Link
Log in

Technologies for Motion Measurements in Connected Health Scenario

  • Chapter
  • First Online:
Connected Health in Smart Cities

  • 1388 Accesses

Abstract

Connected Health, also known as Technology-Enabled Care (TEC), refers to a conceptual model for health management where devices, services, or interventions are designed around the patient’s needs and health-related data is shared in such a way that the patient can receive care in the most proactive and efficient manner. In particular, TEC enables the remote exchange of information, mainly between a patient and a healthcare professional, to monitor health status, and to assist in diagnosis. To that aim recent advances in pervasive sensing, mobile, and communication technologies have led to the deployment of new smart sensors that can be worn without affecting a person’s daily activities. This chapter encompasses a brief literature review on TEC challenges, with a focus on the key technologies enabling the development of wearable solutions for remote human motion tracking. A wireless sensor network-based remote monitoring system, together with the main challenges and limitations that are likely to be faced during its implementation is also discussed, with a glimpse at its application.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. P. Daponte, J. De Marco, L. De Vito, B. Pavic, S. Zolli, Electronic measurements in rehabilitation, in: Proceedings of 2011 IEEE International Symposium on Medical Measurement and Applications (MeMeA), Bari, Italy, May 2011, pp. 274–279

    Google Scholar 

  2. S.F. Jencks, M.V. Williams, E.A. Coleman, Rehospitalizations among patients in the medicare fee-for-service program. New Engl. J. Med. 360(14), 1418–1428 (2009)

    Article  Google Scholar 

  3. N. Gotoda, K. Matsuura, S. Otsuka, T. Tanaka, Y. Yano, Remote training-support of running form for runners with wireless sensor, in: 2010 Proceedings of International Conference on Computers in Education, Putrajaya, Malaysia, pp. 417–421

    Google Scholar 

  4. S. Patel, H. Park, P. Bonato, L. Chan, M. Rodgers, A review of wearable sensors and systems with application in rehabilitation. J. Neuroeng. Rehabil. 9(12), 1–17 (2012)

    Google Scholar 

  5. L. De Vito, O. Postolache, S. Rapuano, Measurements and sensors for motion tracking in motor rehabilitation. IEEE Instrum. Meas. Mag. 17, 30–38 (2014)

    Article  Google Scholar 

  6. S. Sessa, M. Zecca, Z. Lin, T. Sasaki, K. Itoh, A. Takanishi, Waseda bioinstrumentation system #3 as a tool for objective rehabilitation measurement and assessment—development of the inertial measurement unit, in Proceedings of 2009 IEEE International Conference on Rehabilitation Robotics, Kyoto, Japan, June 2009, pp. 115–120

    Google Scholar 

  7. E. Zubiete, L. Luque, A. Rodriguez, I. Gonzalez, Review of wireless sensors networks in health applications, in: Proceedings of 2011 Annual International Conference on in Engineering in Medicine and Biology Society, Boston, MA, USA, September 2011, pp. 1789–1793

    Google Scholar 

  8. C. Chen, C. Pomalaza-Raez, Design and evaluation of a wireless body sensor system for smart home health monitoring, in Proceedings of IEEE Global Telecommunications Conference, Honolulu, HI, USA, December 2009, pp. 1–6

    Google Scholar 

  9. F. Rahimi, C. Duval, M. Jog, C. Bee, A. South, M. Jog, R. Edwards, P. Boissy, Capturing whole-body mobility of patients with Parkinson disease using inertial motion sensors: Expected challenges and rewards, in Proceedings of 2011 Annual International Conference in Engineering in Medicine and Biology Society (EMBC), Boston, MA, USA, 2011, pp. 5833–5838

    Google Scholar 

  10. G.V. Merrett, M. Ettabib, C. Peters, G. Hallett, N. White, Augmenting forearm crutches with wireless sensors for lower limb rehabilitation. Meas. Sci. Technol. 21(12)

    Article  Google Scholar 

  11. J. Neville, A. Wixted, D. Rowlands, D. James, Accelerometers: An underutilized resource in sports monitoring, in Proceedings of 2010 International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Brisbane, Australia, December 2011, pp. 287–290

    Google Scholar 

  12. A.F. Smeaton, D. Diamond, P. Kelly, K. Moran, K.T. Lau, D. Morris, N. Moyna, N.E. O’Connor, K. Zhang, Aggregating multiple body sensors for analysis in sports, in Proceedings of 5th International Workshop on Wearable Micro and Nanosystems for Personalised Health, Valencia, Spain, May 2008, pp. 1–5

    Google Scholar 

  13. M.A. Brodie, A. Walmsley, W. Page, The static accuracy and calibration of inertial measurement units for 3d orientation. Comput. Methods Biomech. Biomed. Engin. 11(6), 641–648 (2008)

    Article  Google Scholar 

  14. G.X. Lee, K.S. Low, T. Taher, Unrestrained measurement of arm motion based on a wearable wireless sensor network. IEEE Trans. Instrum. Meas. 59(5), 1309–1317 (2010)

    Article  Google Scholar 

  15. P. Daponte, L. De Vito, C. Sementa, A wireless-based home rehabilitation system for monitoring 3D movements, in Proceedings of 2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Gatineau, Canada, 4–5 May 2013, pp. 282–287

    Google Scholar 

  16. P. Daponte, L. De Vito, C. Sementa, Validation of a home rehabilitation system for range of motion measurements of limb functions, in Proceedings of 2013 IEEE International Symposium on Medical Measurement and Applications, Gatineau, Canada, 2013, pp. 288–293

    Google Scholar 

  17. S. Movassaghi, M. Abolhasan, J. Lipman, D. Smith, A. Jamalipour, Wireless body area networks: A survey. IEEE Commun. Surv. Tutor. 16(3), 1658–1686 (2014)

    Article  Google Scholar 

  18. P. Daponte, L. De Vito, M. Riccio, C. Sementa, Design and validation of a motion-tracking system for rom measurements in home rehabilitation. Measurement 55, 82–96 (2014)

    Article  Google Scholar 

  19. J.B. Kuipers, Quaternions and Rotation Sequences : A Primer with Applications to Orbits, Aerospace, and Virtual Reality (Princeton Univ. Press, Princeton, NJ, 1999)

    MATH  Google Scholar 

  20. J.L. Marins, X. Yun, E.R. Bachmann, R. McGhee, M.J. Zyda, An extended kalman filter for quaternion-based orientation estimation using Marg sensors, in Proceedings of 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, HI, USA, 2001, pp. 2003–2011

    Google Scholar 

  21. X. Yun, E.R. Bachmann, R.B. McGhee, A simplified quaternion-based algorithm for orientation estimation from earth gravity and magnetic field measurements. IEEE Trans. Instrum. Meas. 57(3), 638–650 (2008)

    Article  Google Scholar 

  22. P. Daponte, L. De Vito, G. Mazzilli, S. Rapuano, C. Sementa, Investigating the on-board data processing for IMU-based sensors in motion tracking for rehabilitation, in Proceedings of IEEE International Symposium on Medical Measurement and Applications, Torino, Italy, May 2015, pp. 645–650

    Google Scholar 

  23. J. Grubert, T. Langlotz, S. Zollmann, H. Regenbrecht, Towards pervasive augmented reality: Context- awareness in augmented reality. IEEE Trans. Vis. Comput. Graph. 23(6), 1706–1724 (2017)

    Article  Google Scholar 

  24. L. De Vito, G. Mazzilli, M. Riccio, C. Sementa, Improving the orientation estimation in a packet loss-affected wireless sensor network for tracking human motion, in Proceedings of 21st IMEKO TC4 International Symposium on Understanding the World through Electrical and Electronic Measurement, Budapest, Hungary, September 2016, pp. 184–189

    Google Scholar 

  25. M. Hassanalieragh, A. Page, T. Soyata, G. Sharma, M. Aktas, G. Mateos, B. Kantarci, S. Andreescu, Health monitoring and management using Internet-of-Things (IoT) sensing with cloud-based processing: Opportunities and challenges, in 2015 Proceedings of IEEE International Conference on Services Computing, pp. 285–292

    Google Scholar 

  26. L. Wei, N. Kumar, V. Lolla, E. Keogh, S. Lonardi, C. Ratanamahatana, H. Van Herle, A practical tool for visualizing and data mining medical time series, in Proceedings of 18th IEEE Symposium on Computer-Based Med. Sys., June 2005, pp. 341–346

    Google Scholar 

  27. M. Bazzani, D. Conzon, A. Scalera, M. Spirito, C. Trainito, Enabling the IoT paradigm in e-health solutions through the VIRTUS middleware, in Proceedings of IEEE 11th International Conference on Trust, Security and Privacy in Computing and Com. (TrustCom), June 2012, pp. 1954–1959

    Google Scholar 

  28. N. Bui, M. Zorzi, Health care applications: A solution based on the internet of things, in Proceedings. of 4th International Symposium on Applied Sciences in Biomed. and Com. Tech., New York, USA, 2011, pp. 1–5

    Google Scholar 

  29. L. De Vito, F. Lamonaca, G. Mazzilli, M. Riccio, D.L. Carnì, P.F. Sciammarella, An IoT-enabled multi-sensor multi-user system for human motion measurements, in 2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Rochester, USA, May 2017, pp. 210–215

    Google Scholar 

  30. L. De Vito, S. Rapuano, L. Tomaciello, One-way delay measurement: State of the art. IEEE Trans. Instrum. Meas. 57(12), 2742–2750 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Engineering, University of Sannio, Benevento, Italy

    Pasquale Daponte, Luca De Vito, Gianluca Mazzilli, Sergio Rapuano & Ioan Tudosa

Authors
  1. Pasquale Daponte
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Luca De Vito
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gianluca Mazzilli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sergio Rapuano
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ioan Tudosa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sergio Rapuano .

Editor information

Editors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada

    Abdulmotaleb El Saddik

  2. Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

    M. Shamim Hossain

  3. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada

    Burak Kantarci

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Daponte, P., De Vito, L., Mazzilli, G., Rapuano, S., Tudosa, I. (2020). Technologies for Motion Measurements in Connected Health Scenario. In: El Saddik, A., Hossain, M., Kantarci, B. (eds) Connected Health in Smart Cities. Springer, Cham. https://doi.org/10.1007/978-3-030-27844-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27844-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27843-4

  • Online ISBN: 978-3-030-27844-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics