Literature DB >> 3578961

A Monte Carlo technique for signal level detection in implanted intracranial pressure monitoring.

R K Avent, J D Charlton, H T Nagle, R N Johnson.   

Abstract

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.

Mesh:

Year:  1987        PMID: 3578961     DOI: 10.1007/bf02364169

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  4 in total

1.  Trend detection of pseudo-random variables using a exponentially mapped past statistical approach: an adjunct to computer assisted monitoring.

Authors:  D J Hitchings; M J Campbell; D E Taylor
Journal:  Int J Biomed Comput       Date:  1975-04

2.  Statistical monitoring techniques.

Authors:  C D Lewis
Journal:  Med Biol Eng       Date:  1971-07

3.  A nonlinear analysis of the cerebrospinal fluid system and intracranial pressure dynamics.

Authors:  A Marmarou; K Shulman; R M Rosende
Journal:  J Neurosurg       Date:  1978-03       Impact factor: 5.115

Review 4.  Time series methods in the monitoring of intracranial pressure. Part 1: Problems, suggestions for a monitoring scheme and review of appropriate techniques.

Authors:  R Allen
Journal:  J Biomed Eng       Date:  1983-01
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.