Title :
Intracranial pressure signals forecasting with wavelet transform and neuro-fuzzy network
Author :
Azzerboni, B. ; Finocchio, G. ; Ipsale, M. ; Foresta, F. La ; Morabito, F.C.
Author_Institution :
DFMTFA, Messina Univ., Italy
Abstract :
In this paper, we propose a novel approach to forecast the time evolution of the intracranial pressure (ICP) signal acquired by means of optical fiber catheters in patients with neurological pathologies. The proposed processing system uses wavelet transform and neuro-fuzzy network (NFN) to make the forecast. It is noteworthy to underline that a forecasting approach based only on NFN would provide information limited to a few samples. The advantage of this method is that it turns to account both the wavelet ability to focus information in few parameters and the NFN performance to expand the forecasting to a larger set, improving the agreement between the experimental data and the predicted ones.
Keywords :
brain; diseases; fuzzy neural nets; medical signal processing; wavelet transforms; cerebral blood flow; cerebral perfusion pressure; dynamic equilibrium; intracranial components; intracranial pressure signal time evolution; intracranial pressure signals; intracranial volume; neuro-fuzzy network; neurological pathologies; neurosurgery problems; optical fiber catheters; skull; Biological neural networks; Brain; Catheters; Cranial pressure; Discrete wavelet transforms; Fuzzy logic; Fuzzy neural networks; Pathology; Uniform resource locators; Wavelet transforms;
Conference_Titel :
Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint
Print_ISBN :
0-7803-7612-9
DOI :
10.1109/IEMBS.2002.1106419