activity
20212026
most citedSparse learned kernels for interpretable and efficient medical time series processing

14 citations · 27 across the 11 of their papers we have counts for

collaborators
Showing eess.SPShow all

8 papers · 1 filter

eess.SP2026

CAP: Towards PPG Universal Representation Learning with Patient-level Supervision

Chenyang He, Xinyi Shao, Shun Huang +4

Photoplethysmography (PPG) plays a central role in wearable health monitoring and clinical decision support. Yet existing approaches to universal PPG representation learning largel…

eess.SP2024★ 1 cited

SiamQuality: A ConvNet-Based Foundation Model for Imperfect Physiological Signals

Cheng Ding, Zhicheng Guo, Zhaoliang Chen +3

Foundation models, especially those using transformers as backbones, have gained significant popularity, particularly in language and language-vision tasks. However, large foundati…

eess.SP2024★ 1 cited

SQUWA: Signal Quality Aware DNN Architecture for Enhanced Accuracy in Atrial Fibrillation Detection from Noisy PPG Signals

Runze Yan, Cheng Ding, Ran Xiao +4

Atrial fibrillation (AF), a common cardiac arrhythmia, significantly increases the risk of stroke, heart disease, and mortality. Photoplethysmography (PPG) offers a promising solut…

eess.SP2023

Photoplethysmography based atrial fibrillation detection: an updated review from July 2019

Cheng Ding, Ran Xiao, Weijia Wang +2

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant health ramifications, including an elevated susceptibility to ischemic stroke, heart disease,…

eess.SP2023★ 2 cited

A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearables

Pranay Jain, Cheng Ding, Cynthia Rudin +1

Smart watches and other wearable devices are equipped with photoplethysmography (PPG) sensors for monitoring heart rate and other aspects of cardiovascular health. However, PPG sig…

eess.SP2023★ 14 cited

Sparse learned kernels for interpretable and efficient medical time series processing

Sully F. Chen, Zhicheng Guo, Cheng Ding +2

Rapid, reliable, and accurate interpretation of medical time-series signals is crucial for high-stakes clinical decision-making. Deep learning methods offered unprecedented perform…

eess.SP2022★ 2 cited

Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection using Eight Million Samples Labeled with Imprecise Arrhythmia Alarms

Cheng Ding, Zhicheng Guo, Cynthia Rudin +7

Atrial fibrillation (AF) is a common cardiac arrhythmia with serious health consequences if not detected and treated early. Detecting AF using wearable devices with photoplethysmog…

eess.SP2021★ 4 cited

Log-Spectral Matching GAN: PPG-based Atrial Fibrillation Detection can be Enhanced by GAN-based Data Augmentation with Integration of Spectral Loss

Cheng Ding, Ran Xiao, Duc Do +4

Photoplethysmography (PPG) is a ubiquitous physiological measurement that detects beat-to-beat pulsatile blood volume changes and hence has a potential for monitoring cardiovascula…