A MONTE-CARLO TECHNIQUE FOR SIGNAL LEVEL DETECTION IN IMPLANTED INTRACRANIAL-PRESSURE MONITORING

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 is 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.