A Monte Carlo technique for signal level detection in implanted intracranial pressure monitoring
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Statistical monitoring techniques like CUSUM, Trigg's tracking signal and EMP filtering have a major advantage over more recent techniques, such as Kalman filtering, because of their inherent simplicity. In many biomedical applications, such as electronic implantable devices, these simpler techniques have greater utility because of the reduced requirements on power, logic complexity and sampling speed. The determination of signal means using some of the earlier techniques are reviewed in this paper, and a new Monte Carlo based method with greater capability to sparsely sample a waveform and obtain an accurate mean value is presented. This technique may find widespread use as a trend detection method when reduced power consumption is a requirement.
KeywordsTrend detection Monte Carlo method Time series analysis ICP sampling
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- 2.Harrison, P.J. and O.L. Davies. The use of cumulative sum (CUSUM) techniques for the control of routine forecasts of product demand.Operations Res. 12:325–333, 1963.Google Scholar
- 3.Hitchings, D.J., M.J. Campbell and D.E.M. Taylor. Trend detection of pseudo-random variables using an exponentially mapped past statistical approach: An adjunct to computer assisted monitoring.Int. J. Bio-Medical Computing 6:73–87, 1975.Google Scholar
- 4.Kahn, H.Symposium on Monte Carlo Methods. New York: Wiley, 1956.Google Scholar
- 5.Lewis, C.D. Statistical monitoring techniques.Med. and Biol. Eng., 9:315–323, 1971.Google Scholar
- 6.Martin, F.F.Computer Modeling and Simulation. New York: Wiley, 1968.Google Scholar
- 8.Nyquist, H. Certain topics in telegraph transmission theory.Trans. AIEE 47:617–644, 1928.Google Scholar
- 9.Organick, E.I. and L.P. Meissner.Fortran IV. Reading, MA: Addison-Wesley, 1974.Google Scholar
- 10.Szweczykowski, J., J. Korsak-Sliwka, A. Kunicki, S. Sliwka, J. Dziduszka and P. Dytoko.Intracranial Pressure IV. New York: Springer Verlag 1980, 419–422.Google Scholar
- 11.Trigg, D.W. Monitoring a forecasting system.Opl. Res. Q. 15:271–274, 1964.Google Scholar