By Topic

Input-Feature Correlated Asynchronous Analog to Information Converter for ECG Monitoring

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
$33 $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

2 Author(s)
Ritika Agarwal ; Nanoscale Integrated Sensors and Circuits Laboratory, Tufts University, Medford, U.S.A. ; Sameer Sonkusale

This paper illustrates an architectural design of a novel variable input-feature correlated asynchronous sampling and time-encoded digitization approach for source compression and direct feature extraction from physiological signals. The complete architecture represents an analog-to-information (A2I) converter, designed for ultra-low-power mixed-signal very-large-scale integrated implementation. The device will be suitable for long-term wearable monitoring of physiological signals, such as electrocardiogram (ECG). We show representative case studies on QRS detection in an ECG signal utilizing the proposed A2I converter to prove the functionality of the design. Simulation results show large source compression in the ECG signal and more than 98% efficiency in the detection of the Q, R, and S waves for challenging ECG waveforms, all with extremely low-power and storage requirements.

Published in:

IEEE Transactions on Biomedical Circuits and Systems  (Volume:5 ,  Issue: 5 )