The objective of medical care services is designed to bring improvement to the health of patients. This is pursued with great vigor today with the use of modern health care systems which include medical sensors and automatically controlled actuation to deliver smart and proactive health services. The embedded devices control Smart Medical Devices (SMDs) used by physicians, Nurses, and Medical Staff which continuously interact with the human body or patient in one form or another. Cyber-Physical Systems (CPS) are integrations of computation with physical processes which are monitored and controlled by the embedded systems. CPS has positively affected a number of application areas which include communication, consumer energy, infrastructure, healthcare, manufacturing, military, robotics and transportation. The inappropriate use of these SMDs generate errors which are under-emphasized by stakeholders. Most users are only interested on the benefits derived in the use of SMDs and care-less on the danger that these devices can contribute to patients when used inappropriately. The error tendencies, possible factors and way forward is the subject matter of this paper. In order to achieve the stated objective, Input data was provided through a critical incident analysis of online database which provide readings from medical experts. These readings were compared to the standard world benchmarks and best practices. The difference between the readings and the standard benchmark were used to validate the existence of errors. A framework was developed for error prediction to improve safety in the use of SMDs. Due to the complexity of the problem, an algorithm was further developed to obtain an optimal solution of P1 to P5 within an acceptable threshold runtime which shows the gravity of these challenges on patients.
| Published in | American Journal of Software Engineering and Applications (Volume 4, Issue 4) |
| DOI | 10.11648/j.ajsea.20150404.12 |
| Page(s) | 71-79 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Cyber Physical Systems, Embedded System, SMDs
| [1] | M. Weiser, "Ubiquitous computing" http://www.ubiq.com/hypertext/weiser/UbiHome.html., 2003 |
| [2] | U. Hansmann, "Design Personal Computer real- time and embedded systems Wireless". Springer- Verlag New York, Inc., New York, 2001. |
| [3] | J. Burkhardt, "Pervasive Computing: Technology and Architecture of Mobile Internet Application" Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, 2001. |
| [4] | P. E. N.V. Koninklijke, Ambient intelligence. http://www.research.philips.com/technologies/projects/ambintel.html., 2003 |
| [5] | S. Marzano, and E. Aarts, The New Every day. 010 Publishers, 2003. |
| [6] | E. A. Lee. "Cyber physical systems: design challenges" Technical report, EECS Department, University of California, Berkeley, January (CPS Steering Group), 2008. |
| [7] | Workshop Report. Foundations for Innovation in Cyber-Physical Systems. http://events.energetics.com/NIST- CPS Workshop/downloads.html |
| [8] | D.C. Stockwell, & A. D. Slonim. Quality and safety in the Intensive Care Unit. J Intensive Care Med 2006 Jul; 21(4):199-210. |
| [9] | M. Paolo. Formal verification of Medical user interface software in PVS, Queen Mary University of London, 2014. |
| [10] | NAP Committee on Quality of Health Care in America IoM. ‘To err is human: building a Safer Health System’. Washington, D.C.: National Academy Press, 2001 |
| [11] | M. Soares, J.I.F, Salluh,., F.A. & Bozza, Current definitions of patient safety. In: Chiche, J. D, Moreno R, Putensen C, Rhodes A, editors. Patient Safety and Quality of Care in Intensive Care Medicine. Berlin: Medizinisch Wissenschaftliche Verlagsgesellschaft; p. 9-17. 2009. |
| [12] | T. J., John, A New Evidence-based Estimate of Patient Harms Associated with Hospital Care Journal of Patient Safety Volume 9, Number 3. 2013 |
| [13] | R. Mohamed, and A. Khalid "Development of an expert system for Reducing medical errors" International Journal of Software Engineering & Applications (IJSEA), Vol.4, No.6, November 2013 DOI : 0.5121/ijsea.2013.460329 |
| [14] | R. J. Arney, J. Paul, L. Insup, R. Arnab, S., Oleg, and Z., Yi, Generic Infusion Pump Hazard Analysis and Safety Requirements Version 1.0, 2009 |
| [15] | S. Sriram, H., Hadjar, and L., Clayton. Model- Based Dependability Analysis of Programmable Drug Infusion Pumps University of Colorado, Boulder, CO, 2011. |
| [16] | H. Vaishali, R., Philips, and R. Dev. Design for Reliability in Medical Devices Patient System Safety 978-1-4244-5103- 6/10/$26.00 ©2010 IEEE, 2010 |
| [17] | B. C. Jeffrey, S. N., Ronald, D.L., Charlene, and M., Bucknam, Preventable anesthesia mishaps: a study of human factors. Qual Saf Health Care 2002;11:277–283 https://www.bu.edu/av/courses/med/05sprgmedanes thesiology/002/cooper%20study.pdf, |
| [18] | O. R. Selwyn, M. K. Gawande, P. Ann Louise, Y. Catherine, A.B. Troyen, and M.C. David, Analysis of surgical errors in closed malpractice claims at 4 liability insurers. Harvard Risk Management Foundation and the Harvard School of Public Health, 2006 |
| [19] | C. H. Gaylene, M. H. Fanzca, M.S. Penelope, D.T. and T. Rowan. Barriers to Adverse Event and Error Reporting in Anesthesia. International Anesthesia Research Society, 2012 http://citeseerx.ist.psu.edu/viewdoc/download? doi=10.1.1.380.1686&rep=rep1&type=pdf |
| [20] | FDA. Infusion Pump Improvement Initiative Center for Devices and Radiological Health U.S. Food and Drug Administration 2010. |
| [21] | E. Joan, and L. Helen "Insulin Pump Workbook" (n.d) 5 www.diabetes- education.net/pdf/resources/insulin_pump_workbook.pdf. |
APA Style
Sunday Anuoluwa Idowu, Olawale Jacob Omotosho, Olusegun Ayodeji Ojesanmi, Stephen Olusola Maitanmi. (2015). Cyber-Physical Systems: A Framework for Prediction of Error in Smart Medical Devices. American Journal of Software Engineering and Applications, 4(4), 71-79. https://doi.org/10.11648/j.ajsea.20150404.12
ACS Style
Sunday Anuoluwa Idowu; Olawale Jacob Omotosho; Olusegun Ayodeji Ojesanmi; Stephen Olusola Maitanmi. Cyber-Physical Systems: A Framework for Prediction of Error in Smart Medical Devices. Am. J. Softw. Eng. Appl. 2015, 4(4), 71-79. doi: 10.11648/j.ajsea.20150404.12
AMA Style
Sunday Anuoluwa Idowu, Olawale Jacob Omotosho, Olusegun Ayodeji Ojesanmi, Stephen Olusola Maitanmi. Cyber-Physical Systems: A Framework for Prediction of Error in Smart Medical Devices. Am J Softw Eng Appl. 2015;4(4):71-79. doi: 10.11648/j.ajsea.20150404.12
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Download@article{10.11648/j.ajsea.20150404.12,
author = {Sunday Anuoluwa Idowu and Olawale Jacob Omotosho and Olusegun Ayodeji Ojesanmi and Stephen Olusola Maitanmi},
title = {Cyber-Physical Systems: A Framework for Prediction of Error in Smart Medical Devices},
journal = {American Journal of Software Engineering and Applications},
volume = {4},
number = {4},
pages = {71-79},
doi = {10.11648/j.ajsea.20150404.12},
url = {https://doi.org/10.11648/j.ajsea.20150404.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20150404.12},
abstract = {The objective of medical care services is designed to bring improvement to the health of patients. This is pursued with great vigor today with the use of modern health care systems which include medical sensors and automatically controlled actuation to deliver smart and proactive health services. The embedded devices control Smart Medical Devices (SMDs) used by physicians, Nurses, and Medical Staff which continuously interact with the human body or patient in one form or another. Cyber-Physical Systems (CPS) are integrations of computation with physical processes which are monitored and controlled by the embedded systems. CPS has positively affected a number of application areas which include communication, consumer energy, infrastructure, healthcare, manufacturing, military, robotics and transportation. The inappropriate use of these SMDs generate errors which are under-emphasized by stakeholders. Most users are only interested on the benefits derived in the use of SMDs and care-less on the danger that these devices can contribute to patients when used inappropriately. The error tendencies, possible factors and way forward is the subject matter of this paper. In order to achieve the stated objective, Input data was provided through a critical incident analysis of online database which provide readings from medical experts. These readings were compared to the standard world benchmarks and best practices. The difference between the readings and the standard benchmark were used to validate the existence of errors. A framework was developed for error prediction to improve safety in the use of SMDs. Due to the complexity of the problem, an algorithm was further developed to obtain an optimal solution of P1 to P5 within an acceptable threshold runtime which shows the gravity of these challenges on patients.},
year = {2015}
}
TY - JOUR T1 - Cyber-Physical Systems: A Framework for Prediction of Error in Smart Medical Devices AU - Sunday Anuoluwa Idowu AU - Olawale Jacob Omotosho AU - Olusegun Ayodeji Ojesanmi AU - Stephen Olusola Maitanmi Y1 - 2015/08/19 PY - 2015 N1 - https://doi.org/10.11648/j.ajsea.20150404.12 DO - 10.11648/j.ajsea.20150404.12 T2 - American Journal of Software Engineering and Applications JF - American Journal of Software Engineering and Applications JO - American Journal of Software Engineering and Applications SP - 71 EP - 79 PB - Science Publishing Group SN - 2327-249X UR - https://doi.org/10.11648/j.ajsea.20150404.12 AB - The objective of medical care services is designed to bring improvement to the health of patients. This is pursued with great vigor today with the use of modern health care systems which include medical sensors and automatically controlled actuation to deliver smart and proactive health services. The embedded devices control Smart Medical Devices (SMDs) used by physicians, Nurses, and Medical Staff which continuously interact with the human body or patient in one form or another. Cyber-Physical Systems (CPS) are integrations of computation with physical processes which are monitored and controlled by the embedded systems. CPS has positively affected a number of application areas which include communication, consumer energy, infrastructure, healthcare, manufacturing, military, robotics and transportation. The inappropriate use of these SMDs generate errors which are under-emphasized by stakeholders. Most users are only interested on the benefits derived in the use of SMDs and care-less on the danger that these devices can contribute to patients when used inappropriately. The error tendencies, possible factors and way forward is the subject matter of this paper. In order to achieve the stated objective, Input data was provided through a critical incident analysis of online database which provide readings from medical experts. These readings were compared to the standard world benchmarks and best practices. The difference between the readings and the standard benchmark were used to validate the existence of errors. A framework was developed for error prediction to improve safety in the use of SMDs. Due to the complexity of the problem, an algorithm was further developed to obtain an optimal solution of P1 to P5 within an acceptable threshold runtime which shows the gravity of these challenges on patients. VL - 4 IS - 4 ER -
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