By Topic

A low-power network for on-line diagnosis of heart patients

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Coggins, R. ; Syst. Eng. & Design Autom. Lab., Sydney Univ., NSW, Australia ; Jabri, M. ; Flower, B. ; Pickard, S.

Implantable cardioverter defibrillators detect and treat dangerous cardiac arrhythmias. Current ICDs, however, cannot distinguish between some potentially fatal arrhythmias and benign conditions. Our system classifies intracardiac electrograms to detect such arrhythmias and uses analog techniques to meet the strict power and area requirements of implantable systems. A robust neural network architecture reduces the impact of noise, drift, and offsets inherent in analog approaches

Published in:

Micro, IEEE  (Volume:15 ,  Issue: 3 )