Remote medical monitoring and advisory using artificial intelligence techniques to support operators of transportation equipment

• Autorzy: Czejdo B. , Baszun M.
• Języki publikacji: EN

Abstrakty

EN

Paper discussed new technological advances in design and implementation of remote monitoring systems for operators of transportation equipment. In this presentation we concentrated on monitoring and processing of data described by various medical input parameters such as real time signal from electronic measuring devices. The input can also include subjective parameters specified by the operator of transportation equipment e.g. general feeling, pain etc. In addition, there are other medical parameters such as medications taken, previous diagnosis etc. Data from a remote patient monitoring system can be processed using Artificial Intelligence techniques to generate medical advisory messages.

Słowa kluczowe

EN

artificial intelligence; remote monitoring system; transportation

PL

sztuczna inteligencja; zdalne monitorowanie; transport

• Wydawca: Instytut Naukowo-Wydawniczy "SPATIUM". sp. z o.o.
• Czasopismo: Autobusy : technika, eksploatacja, systemy transportowe
• Rocznik: 2016
• Tom: R. 17, nr 12
• Strony: 107--111
• Opis fizyczny: Bibliogr. 13 poz., rys., tab., wykr.

Twórcy

autor

Czejdo B.

• Department of Mathematics and Computer Science, Fayetteville State University, USA

autor

Baszun M.

• Department of Computer Science, Pawel Wlodkowic University College in Plock and Faculty of Electronics and Information Technology Warsaw University of Technology

Bibliografia

• 1. Truck Driver Health Insurance, Published online 10/15/2016. http://www.truckingsos.com/health-insurance-for-truck-drivers-4/.
• 2. Rama Greenfield,1 Ellen Busink,1 Cybele P. Wong,1 Eva Riboli-Sasco,1 Geva Greenfield,1 Azeem Majeed,1 Josip Car,1,2 and Petra A. Wark, “Truck drivers’ perceptions on wearable devices and health promotion: a qualitative study”, BMC Public Health. 2016; 16: 677. Published online 2016 Jul 30. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967500/
• 3. Roncagliolo, P., Arredondo, L., and Gonzalez A. 2007. Biomedical Signal Acquisition, Processing and Transmission Using Smartphone. In Proceedings of the 16th Argentine Bioengineering Congress and the 5th Conference of Clinical Engineering. Journal of Physics: Conference Series, 90, 2007. DOI=10.1088/1742-6596/90/1/012028.
• 4. Zhang, P., Kogure, Y., Matsuoka, H., Akutagawa, M., Kinouchi, Y., and Zhang, Q. 2007. A Remote Patient Monitoring System Using a Java-enabled 3G Mobile Phone. In Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France, August 23--26, 2007.
• 5. Sufi, F., Fang, Q., and Cosic I. 2007. ECG R-R Peak Detection on Mobile Phones. In Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France, August 23--26, 2007.
• 6. Kacki E., Kulikowski L., Nowakowski A., Waniewski E.: „Systemy komputerowe i teleinformatyczne w sluzbie zdrowia”, Akademicka Oficyna Wydawnicza EXIT, Warszawa 2002.
• 7. Baszun M., Glówka M.: “An Internet expert system based on fuzzy sets and fuzzy logic for telemedicine applications”, XV Konferencja Inzynierii Akustycznej i Biomedycznej, Zakopane, April 2008, Poland.
• 8. Baszun M.: “A real time telemedicine system for wireless monitoring of outdoor patients based on internet and cell telephone nets”, Dni Nauki I Technologii, Bialowieza, October 2007, Poland.
• 9. Szewczyk P., Baszun M., “The Learning System by Least Squares Support Vector Machine Method and Application in Medicine”, JOURNAL OF TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY, nr. 3, 2011, ISSN 1509-4553.
• 10. Baszun M. Czejdo B., Kuc Ł., “TestedBed System for Soft Computing with Neural Networks”, Book Chapter in: Wenqin Zhang (Ed.) “FUTURE COMMUNICATION AND COMPUTER TECHNOLOGY, ICFCCT 2012”, Edited by Science Technology Press Co. Limited, Honk Kong, 2012, ISBN 978-988-15121-4-7.
• 11. Zdzislaw Pawlak, Andrzej Skowron: Rough sets and Boolean reasoning. Inf. Sci. 177(1): 41-73 (2007).
• 12. Zdzislaw Pawlak: Flow Graphs and Intelligent Data Analysis. Fundam. Inform. 64(1-4): 369-377 (2005).
• 13. S.Russell and P. Norvig, Artificial Intelligence A modern Approach, Prentice Hall, 2003.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).