Design of a VLSI neural network arrhythmia classifier

Author

Shawkey, H. ; Elsimary, H. ; Haddara, H. ; Ragaie, H.F.

Author_Institution

Dept. of Electron. Res. Inst. Microelectron., Ain Shams Univ., Cairo, Egypt

fYear

1999

fDate

23-25 Feb 1999

Abstract

Artificial neural networks are now attractive tools to enhance and improve the efficiency, the capability and the features of instrumentation in applications related to measurements, system identification, and control. The aim of this paper is to implement an implantable cardiverter defibrillator (ICD) using an analog neural network. The paper describes a VLSI neural network chip to be implemented using 1.2 μm CMOS technology, which acts as an intracardiac tachycardia classification system. A robust neural network is less sensitive to noise, drift and offsets inherent in analog applications. The proposed classifier uses two types of neural networks a Kohonen self organizing map (KSOM) circuit and a winner take all (WTA) circuit

Keywords

CMOS analogue integrated circuits; VLSI; biomedical equipment; biomedical measurement; defibrillators; electrocardiography; medical signal processing; neural chips; patient monitoring; prosthetics; self-organising feature maps; signal classification; 1.2 micron; CMOS technology; Kohonen self organizing map circuit; VLSI neural network arrhythmia classifier; VLSI neural network chip; analog neural network design; artificial neural networks; implantable cardioverter defibrillator; instrumentation; intracardiac tachycardia classification system; measurements; system control; system identification; winner take all circuit; Artificial neural networks; CMOS technology; Circuits; Control systems; Instruments; Neural networks; Paper technology; Semiconductor device measurement; System identification; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Radio Science Conference, 1999. NRSC '99. Proceedings of the Sixteenth National

Conference_Location

Cairo

Print_ISBN

977-5031-62-1

Type

conf

DOI

10.1109/NRSC.1999.760911

Filename

760911