Real-time detection of epileptogenic discharges using autoregressive prediction

Author

Johnson, C. ; Martino, R.L. ; Yap, T.

Author_Institution

Comput. Syst. Lab., Nat. Inst. of Health, Bethesda, MD, USA

fYear

1990

fDate

26-27 Mar 1990

Firstpage

89

Lastpage

90

Abstract

An algorithm is presented that detects epileptogenic discharges from the electroencephalograph (EEG) and magnetoencephalograph (MEG) signals of an epileptic patient in real time using autoregressive prediction in conjunction with an adaptive binomial decision rule. This algorithm is implemented on a personal computer system that performs the data acquisition and discharge detection and extraction functions. Testing with both simulated and real patient data shows this method to be useful for real-time epileptogenic discharge detection

Keywords

biomagnetism; brain; computerised signal processing; electroencephalography; medical diagnostic computing; microcomputer applications; patient monitoring; adaptive binomial decision rule; algorithm; autoregressive prediction; data acquisition; discharge detection; electroencephalograph signals; epileptic patient; extraction functions; magnetoencephalograph signals; personal computer system; real-time epileptogenic discharge detection; Adaptive signal detection; Electroencephalography; Epilepsy; Fault location; IIR filters; Laboratories; Real time systems; Signal detection; Signal processing; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 1990., Proceedings of the 1990 Sixteenth Annual Northeast

Conference_Location

State College, PA

Type

conf

DOI

10.1109/NEBC.1990.66301

Filename

66301