e-G2C: A 0.14-to-8.31 $μ$J/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM

no code implementations • 24 Jul 2022 • Yang Zhao, Yongan Zhang, Yonggan Fu, Xu Ouyang, Cheng Wan, Shang Wu, Anton Banta, Mathews M. John, Allison Post, Mehdi Razavi, Joseph Cavallaro, Behnaam Aazhang, Yingyan Lin

This work presents the first silicon-validated dedicated EGM-to-ECG (G2C) processor, dubbed e-G2C, featuring continuous lightweight anomaly detection, event-driven coarse/precise conversion, and on-chip adaptation.

Anomaly Detection

RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms

no code implementations • 4 Nov 2021 • Yongan Zhang, Anton Banta, Yonggan Fu, Mathews M. John, Allison Post, Mehdi Razavi, Joseph Cavallaro, Behnaam Aazhang, Yingyan Lin

To close this gap and make a heuristic step towards real-time critical intervention in instant response to irregular and infrequent ventricular rhythms, we propose a new framework dubbed RT-RCG to automatically search for (1) efficient Deep Neural Network (DNN) structures and then (2)corresponding accelerators, to enable Real-Time and high-quality Reconstruction of ECG signals from EGM signals.

Navigate Neural Architecture Search

Nonlinear Regression with a Convolutional Encoder-Decoder for Remote Monitoring of Surface Electrocardiograms

no code implementations • 10 Dec 2020 • Anton Banta, Romain Cosentino, Mathews M John, Allison Post, Skyler Buchan, Mehdi Razavi, Behnaam Aazhang

We will achieve this goal with 12-lead ECG reconstruction and by providing a new diagnostic tool for classifying atypical heartbeats.

regression