Skip to main content
SpringerLink
Log in

Smart wearable system for safety-related medical IoT application: case of epileptic patient working in industrial environment

  • Original Paper
  • Published:
Health and Technology Aims and scope Submit manuscript

Abstract

Medical/Industrial IoT is being implemented currently in several domains due to the autonomy it offers to patients, as well as the productivity efficiency that it could enhance. Additionally, the ease of monitoring of the patient, and of action taking in case of sudden medical problems has highlighted the use of such system. The IoT application presented in this paper will target epileptic patients working in an industrial environment. A smart wearable jacket will capture continuously the vital signs of the patient. In case of problem detection, some control signals will be sent to nearby machines to disable them and to alert the medical entities in the working environment. As industrial environments are often safety-critical, the proposed approach is based on basic safety and reliability concepts, which will be enhanced in future works. For this aim, a set of various sensors is used in this work. Although none of the sensors are redundant, all of them give complementary data about the patient health and will insert diversity to the system. A further safety issue consists on using a safety-related processor architecture for processing the sensor data and providing safe outputs.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. World Health Organization (WHO). Epilepsy: the disorder; 2005.

  2. Bazil CW, Friedman D, Chong D. Epilepsy. New York; ISBN: 9780199876785: Oxford University Press; 2011.

    Google Scholar 

  3. Harden C. Complete the following statement: industry-sponsored antiepileptic drug pregnancy registries provide information that is beneficial to: patients doctors the sponsor all of the above none of the above cannot respond due to risk of COI. Epilepsy Currents. 2011;11(6):181–3.

    Article  Google Scholar 

  4. International Electrotechnical Commission IEC/EN 61508. International standard 61508 functional safety: Safety Related systems: Second Edition; Geneva; 2010.

  5. Telawi S, Hayek A, Börcsök J. Safety-related system for detecting and controlling vehicles motion. In: third IEEE International Conference on Technological Advances in Electrical, Electronics and Computer Engineering. Beirut; 2015. p. 80-84.

  6. Preschern C, Kajtazovic N, Kreiner C. Built-in security enhancements for the 1oo2 safety architecture. In: IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems. Bangkok; 2012.

  7. Morley RE, Richter EJ, Klaesner JW, Maluf KS, Mueller MJ. In-shoe multisensory data acquisition system. IEEE Trans Biomed Eng. 2001;48(7):815–20.

    Article  Google Scholar 

  8. Pappas IPI, Keller T, Mangold S. A reliable, gyroscope based gait phase detection sensor embedded in a shoe insole. IEEE Sensors Journal. 2002;2:1085–8.

  9. Bamberg SJM, Benbasat AY, Scarborough DM, Krebs DE, Paradiso JA. Gait analysis using a shoe-integrated wireless sensor system. IEEE Trans Inf Technol Biomed. 2008;12(4):413–23.

    Article  Google Scholar 

  10. Howell AM, Kobayashi T, Chou TR, Daly W, Orendurff M, Bamberg SJM. A laboratory insole for analysis of sensor placement to determine ground reaction force and ankle moment in patients with stroke. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. San Diego, CA; 2012. p 6394-6397.

  11. Howell AM, Kobayashi T, Hayes HA, Foreman KB, Bamberg SJM. Kinetic gait analysis using a low-cost insole. IEEE Trans Biomed Eng. 2013;60(12):3284–90.

    Article  Google Scholar 

  12. Sorensen T, Olsen U, Conradsen I. Automatic epileptic seizure onset detection using matching pursuit: a case study”. Engineering in Medicine and Biology Society (EMBC). Annual International Conference of the IEEE; 2010.

  13. Borujeny GT, Yazdi M, Keshavarz-Haddad A, Borujeny AR. Detection of epileptic seizure using wireless sensor networks. J Med Signals Sens. 2013;3:63–8.

  14. Halabi N, Achkar R, Abi Zeid Daou R, Hayek R, Börcsök J. Design and testing tool for a Safe Monitoring System for Neurodegenerative Disorder Patients – 3rd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA) – July 2016, Lebanon.

  15. Hayek A, Machmur B, Schreiber M, Börcsök J, Gölz S, Epp M. HICore1: “Safety on a chip” turnkey solution for industrial control. In: 25th IEEE International Conference on Application-Specific Systems, Architectures and Processors. Zurich; 2014. p. 74-75.

  16. Shoeb A. Application of machine learning to epileptic seizure onset detection and treatment. PhD Thesis, Massachusetts Institute of Technology; 2009.

Download references

Author information

Authors and Affiliations

  1. Institute for Computer Architecture and System Programming, University of Kassel, Wilhelmshoeher Allee 71, 34121, Kassel, Germany

    Ali Hayek, Samer Telawi & Josef Börcsök

  2. Department of Biomedical Engineering, Lebanese German University, Sahel Alma, Lebanon

    Roy Abi Zeid Daou

  3. Mart, Learning, Education and Research Center, Chananiir, Lebanon

    Roy Abi Zeid Daou

  4. Faculty of Engineering, American University of Science and Technology, Achrafieh, Lebanon

    Nashaat Halabi

Authors
  1. Ali Hayek
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Samer Telawi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Josef Börcsök
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Roy Abi Zeid Daou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nashaat Halabi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ali Hayek.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hayek, A., Telawi, S., Börcsök, J. et al. Smart wearable system for safety-related medical IoT application: case of epileptic patient working in industrial environment. Health Technol. 10, 363–372 (2020). https://doi.org/10.1007/s12553-019-00335-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12553-019-00335-2

Keywords

Search

Navigation