Detection of dynamical transitions in biomedical signals using nonlinear methods

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3215, Issue , 2004, Pages 483-490

  McSharry, Patrick E ^a,b  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b LONDON SCHOOL OF ECONOMICS   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DIAGNOSIS; KNOWLEDGE BASED SYSTEMS; STOCHASTIC SYSTEMS;

BIOMEDICAL SIGNAL; DYNAMICAL TRANSITION; EPILEPTIC SEIZURES; MEDICAL DIAGNOSTICS; MULTI DIMENSIONAL; NON-LINEAR METHODS; NONLINEAR STATISTICS; PROBABILITY EVOLUTION;

BIOELECTRIC PHENOMENA;

EID: 84975462948     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30134-9_65     Document Type: Conference Paper

References (5)

1. McSharry, P.E., He, T., Smith, L.A., Tarassenko, L.: Linear and nonlinear methods for automatic seizure detection in scalp electroencephalogram recordings. Medical & Biological Engineering & Computing 40 (2002) 447–461
2. Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in C. 2nd edn. CUP, Cambridge (1992)
3. Iasemidis, L.D., Sackellares, J.C.: Chaos theory and epilepsy. The Neuroscientist 2 (1996) 118–126
4. (http://www.physionet.org)
5. McSharry, P.E., Smith, L.A., Tarassenko, L.: Prediction of epileptic seizures: are nonlinear methods relevant? Nature Medicine 9 (2003) 241–242