Abstract
The problem of reliable detection of life-threatening situations in the neurosurgical patient undergoing treatment in the ICU is still far from reaching a satisfactory solution, although several methods of clinical and instrumental evaluation have recently been developed for the early detection of oncoming signs of danger. Continuous monitoring of intracranial pressure (ICP) provides neurosurgeons with valuable information about the current condition of the patient. However, it is increasingly felt that traditional methods of extracting information from the ICP signal have reached their natural limits, mostly because of difficulties in fitting the appropriate mathematical model to this nonlinear and non-stationary process. Successful implementations of artificial neural networks in many medical tasks have encouraged the application of this method to ICP processing. Two problems are considered: the prediction of trends in ICP, and recognition of the configuration of unfavourable symptoms likely to signal danger for the neurosurgical patient. The construction of neural network predictors of ICP trends is based on wavelet pre-processing of the original signal. The approach to the second task involves preprocessing of the ICP with spectral and statistical methods and classification of the extracted features of the current signal on an arbitrarily selected scale of danger.
Similar content being viewed by others
References
Baxt, W. G. (1995): ‘Application of neural networks to clinical medicine’,The Lancet,346, pp. 1135–1138
Czosnyka, M., Guazzo, E., Whitehouse, M., Smielewski, P., Czosnyka, Z., Kirkpatrick, P., andPickard, J. D. (1996): ‘Significance of intracranial pressure waveform analysis after head injury’,Acta Neurochirurgica (Wien),138, pp. 531–542
Haykin, S. (1994): ‘Neural networks. A comprehensive foundation’ (Macmillan College Publishing Co., New York)
Pattichis, C. S., andConstantinides, A. G. (1994): ‘Medical imaging with neural networks’.Proc. 1994 IEEE Workshop: Neural networks and signal processing IV, Ermioni, Greece, Sept. 6–8, pp. 431–440
Strang, G., andNguyen, T. (1996): ‘Wavelets and filter banks’ (Wellesley-Cambridge Press, USA)
Swiercz, M., Lewko, J., andMariak, Z. (1995): ‘Application of neural networks to the prediction of intracranial pressure (ICP). A preliminary study’,Biocybern. Biomed. Eng.,15, pp. 93–104
Tsui, F.-C., Sun, M., Li, C.-C., andSclabassi, R. J. (1995): ‘Recurrent neural networks and wavelet transform for time series modelling and prediction’.Proc. IEEE Int. Conf. on Acoustic, speech and signal processing,5, pp. 3359–3362
Yoshiya, J., andTashiro, C. H. (1989): ‘New trends in monitoring in the ICU’,Intensive Care World,6, pp. 61–65
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Swiercz, M., Mariak, Z., Lewko, J. et al. Neural network technique for detecting emergency states in neurosurgical patients. Med. Biol. Eng. Comput. 36, 717–722 (1998). https://doi.org/10.1007/BF02518874
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF02518874