Computer Methods and Programs in Biomedicine 51(1996) 51-73 Non-linear algorithms for processing biological signals S. Cerutti* a , G. Carraultb, P.J.M. Cluitma&, A. Kinieb, T. Lippingd, N. Nikolaidis”, I. Pitas”, M.G. Signorini” ‘Biomedical Engineering Depaltment, Polytechnic lJm’versi~p.za Leonardo da Vinci 32, 20133, Milano, Italy bLaboratoire Traitement du Signal et de l’lmage - CJF-lnsenn 93-04, Vniversite’ de Rennes, I-35042 Rennes Cedex, France ‘Department of Medical Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands ‘Signal Processing Labomtory, Tampere Universiv of Technology, P.O. BOX 5.53, FIN-33101, Tampere, Finland ‘Department of Informatics, Aristotle Universi& of Thessaloniki, Thessaloniki 540 06, Greece Abstract This paper illustrates different approaches to the analysis of biological signals based on non-linear methods. The performance of such approaches, despite the greater methodological and computational complexity is, in many instances, more successful compared to linear approaches, in enhancing important parameters for both physiological studies and clinical protocols. The methods introduced employ median filters for pattern recognition, adaptive segmentation, data compression, prediction and data modelling as well as multivariate estimators in data clustering through median learning vector quantizers. Another approach described uses Wiener-Volterra kernel technique to obtain a satisfactory estimation and causality test among EEG recordings. Finally, methods for the assessment of non-linear dynamic behaviour are discussed and applied to the analysis of heart rate variability signal. In this way invariant parameters are studied which describe non-linear phenomena in the modelling of the physiological systems under investigation. Keywords: Median filtering; Median learning vector quantizers; Wiener-Volterra kernel; Non-linear dynamics; Time-delay estimation; Deterministic chaos *Corresponding author. BiomedicalEngineering Department, Polytechnic University,p.za Leonardo da Vinci 32, 20133 Milano. Italy. Tel: + 39 223993339; fax: + 39 223993360; e-mail: cerutti@icil64.cilea.it 0169-2607/96/$15.00 0 1996Elsevier Science Ireland Ltd. All rights reserved. PII SO I69-2607(96) 01762-2