Apkar Salatian, School of Information Technology and Communications, American University of Nigeria, Yola Bypass, Nigeria
Francis Adepoju, School of Information Technology and Communications, American University of Nigeria, Yola Bypass, Nigeria
The interpretation of high volumes of noisy computerized physiological data generated by the monitors of an Intensive Care Unit (ICU) is complex. To ease the information overload on medical staff we propose a time series analysis technique called data wavelets to derive trends in the data – this will facilitate Clinical Decision Support in the form of qualitative reasoning for patient state assessment. Our approach has been successfully applied to cardiovascular data from a neonatal ICU.
EEG, Graphic Driving Simulator, PPG, Signal System, Yellow Light Dilemma
[1] T. Sukuvaara, M. Sydänmaa, H. Nieminen, A. Heikelä, E. M. J. Koski, Object-Oriented Implementation of an Architecture for Patient Monitoring, IEEE Engineering in Medicine and Biology, pages 69-81, December 1993.
[2] Lambert, C.R., Raymenants, E., Pepin, C.J., Time-Series Analysis of Long-Term Ambulatory Myocardial Ischemia: Effects of Beta-Adrenergic and Calcium Channel Blockage. Am. Heart J. 129, 677-684, 1995.
[3] Imhoff, M., Bauer, M., Gather, U., Lohlein, D., Time Series Analysis in Intensive Care Medicine. Applied Cardiopulmonary Pathophysiology 6, 263-281, 1997.
[4] Fried R., Gather, U., Imhoff M., Pattern Recognition in Intensive Care Online Monitoring. In Schmitt, Manfred., Teodorescu Horia-Nicolai., Jain Ashlesha., Jain Ajita., Jain Sandhya., and Jain Lakhmi. (eds): Studies In Fuzziness and Soft Computing, Computational Intelligence processing in Medical Diagnosis.
Springer-Verlag Company, Chapter 6, pp 129-156, ISSN 1434-9922, ISBN 3-7908-1463-6, Physica-Verlag Heidelberg, New York, 2002.
[5] Amara Graps, Jnl of Computational Science and Engineering, vol. 2, num. 2, published by the IEEE Computer Society, 10662 Los Vaqueros Circle, Los Alamitos, CA 90720, USA, 1995.
[6] Kendall, M., Time Series. London: Charles Griffin, 1973.
[7] Priestley, M.B, Spectral Analysis and Time Series. (Vol. 1): Univariate Series. London: Academic Press, 1981.
[8] Cunningham S., Deere S., Elton R.A., McIntosh N., Neonatal physiological trend monitoring by computer. International Journal of Clinical Monitoring and Computing, 9, 221-227, 1992.
[9] Kohane I. S., Temporal Reasoning in Medical Expert Systems, Boston University School of Medicine, Boston, MA 02118 U.S.A, 1986.
[10] Salatian, A., Interpreting Historical ICU Data Using Associational and Temporal Reasoning, 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2003), Sacramento, California, USA, pages 442-450, ISBN 0-7695-2038-3, ISSN 1082-3409, 3-5 November 2003.
[11] Shahar, Y., A Framework for Knowledge-Based Temporal Abstraction, Artificial Intelligence in Medicine, pp 79-133, 1997.
[12] Salatian A., Hunter, J. R. W., Deriving trends in historical and real-time continuously sampled medical data, Journal of Intelligent Information Systems, 13:47-74, ISSN 0925-9902, 1999.
[13] Kohane, I.S., Haimowitz, I. J., Hypothesis-Driven Data Abstraction with Trend Templates, Symposium on Computer Applications in Medical Care, 1993.
[14] Steimann, F., Adlassnig, K.P., Two-Stage Interpretation of ICU Data Based on Fuzzy Sets, Working Notes of AAAI Spring Symposium Series: Interpreting Clinical Data, pp 152-156, Stanford University, arch 21-23, 1994.
[15] Tak-Wai Hau, D., Learning Qualitative Models from Physiological Signals, Master of Science in Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 1994.
APA:
Salatian, A., & Adepoju, F. (2020). Using Time Series Analysis for Clinical Decision Support. International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, 139, 23-28. doi: 10.33832/ijast.2020.139.03.
MLA:
Salatian, Apkar, et al. “Using Time Series Analysis for Clinical Decision Support.” International Journal of Advanced Science and Technology, ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 139, 2020, pp. 23-28. IJAST, http://article.nadiapub.com/IJAST/Vol139/3.html.
IEEE:
[1] A. Salatian, and F. Adepoju, "Using Time Series Analysis for Clinical Decision Support." International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 139, pp. 23-28, June 2020.
IJAST aims to facilitate and support research related to advanced science and technology and the applications. Our Journal provides a chance for academic and industry professionals to discuss recent progress in the areas of advanced science and technology.
