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Owing to the existence of "reserve spaces" varying individually in extent and expressed by the term compliance, space-consumption intracranial processes do not raise the intracranial pressure (ICP) primarily. Only when this compliance has been exhausted may ICP rise dramatically and may rapidly reach dangerously high levels. It has been shown in the past that "anticipatory" initiation of ICP-reducing measures--i.e. very early in the development of increasing mean ICP--may greatly benefit patient outcome. To recognize an imminent ICP crisis, the available compliance needs to be known. The classical method for determining this latter is the bolus test, which, however, has the disadvantage of being discontinuous and associated with the risk of infection. Another, less invasive and continuous, option is the recognition of pathological intracranial pressure waves. However, recognition of such patterns requires specialized knowledge, that is not widely available. Since, however, knowledge of the compliance is of general importance for intensive care, the idea of developing a PC-based automated system for the identification of pathological waves was followed up. During the course of our basic research effort, we investigated the suitability of the fast Fourier transformation (FFT) algorithm for this purpose. We were able to show that while the FFT is theoretically useful for the detection of pathological intracranial waves, its shortcomings in terms of its sensitivity to extraneous signals (noise) (of considerable importance for biological data handling) and errors in correctly estimating the amplitudes of pathological waves (of great importance for clinical evaluation) make FFT appear less than optimally suitable for this purpose.

biomedizinische technik

Möglichkeiten und Grenzen der automatischen Erkennung pathologischer Hirndruckwellen mittels FFT - Opportunities and Limitations of the Automatic Detection of Pathological Intracranial Pressure Waves with the Aid of Fast Fourier Transformation