from PhysioNet, the research resource for complex physiologic signals


Improving the Quality of ECGs Collected Using Mobile Phones: Papers about the Challenge

The papers below were presented at Computers in Cardiology 2011. Please cite this publication when referencing any of these papers. These papers have been made available by their authors under the terms of the Creative Commons Attribution License 3.0 (CCAL). We wish to thank all of the authors for their contributions.

Update: Inspired by this Challenge, the journal Physiological Measurement has devoted a focus issue [2012 Sept;33(9)] to the subject of signal quality in cardiorespiratory monitoring, with eleven articles on this topic, including nine written by Challenge participants.

The first of these papers is an introduction to the challenge topic, with a summary of the challenge results and a discussion of their implications.

Improving the Quality of ECGs Collected Using Mobile Phones: The PhysioNet/Computing in Cardiology Challenge 2011
Ikaro Silva, George B Moody, Leo Celi

The remaining papers were presented by participants in the Challenge, who describe their approaches to the challenge problem.

CinC Challenge - Assessing the Usability of ECG by Ensemble Decision Trees
Sebastian Zaunseder, Robert Huhle, Hagen Malberg

An Algorithm for Assessment of Quality of ECGs Acquired via Mobile Telephones
Philip Langley, Luigi Y Di Marco, Susan King, David Duncan, Costanzo Di Maria, Wenfeng Duan, Marjan Bojarnejad, Dingchang Zheng, John Allen, Alan Murray

Signal Quality Indices and Data Fusion for Determining Acceptability of Electrocardiograms Collected in Noisy Ambulatory Environments
GD Clifford, D Lopez, Q Li, I Rezek

Assessment of Signal Quality and Electrode Placement in ECGs using a Reconstruction Matrix
Arie C Maan, Erik W van Zwet, Sumche Man, Suzanne MM Oliveira-Martens, Martin J Schalij, Cees A Swenne

ECG Quality Assessment for Patient Empowerment in mHealth Applications
Dieter Hayn, Bernhard Jammerbund, Günter Schreier

Real-time Signal Quality Assessment for ECGs Collected using Mobile Phones
Chengyu Liu, Peng Li, Lina Zhao, Feifei Liu, Ruxiang Wang

Rule-Based Methods for ECG Quality Control
Benjamin E Moody

Electrocardiogram Quality Classification based on Robust Best Subsets Linear Prediction Error
Kai Noponen, Mari Karsikas, Suvi Tiinanen, Jukka Kortelainen, Heikki Huikuri, Tapio Seppänen

Computer Algorithms for Evaluating the Quality of ECGs in Real Time
Henian Xia, Gabriel A Garcia, Joseph C McBride, Adam Sullivan, Thibaut De Bock, Jujhar Bains, Dale C Wortham, Xiaopeng Zhao

Recognition of Diagnostically Useful ECG Recordings: Alert for Corrupted or Interchanged Leads
Irena Jekova, Vessela Krasteva, Ivan Dotsinsky, Ivaylo Christov, Roger Abächerli

Assessment of ECG Quality on an Android Platform
Lars Johannesen

Using Machine Learning to Detect Problems in ECG Data Collection
Nir Kalkstein, Yaron Kinar, Michael Na'aman, Nir Neumark, Pini Akiva

Physionet Challenge 2011: Improving the Quality of Electrocardiography Data Collected Using Real Time QRS-Complex and T-Wave Detection
Thomas Ho Chee Tat, Chen Xiang, Lim Eng Thiam

Could Determination of Equivalent Dipoles from 12 Lead ECG Help in Detection of Misplaced Electrodes
Vito Starc

Simple Scoring System for ECG Quality Assessment on Android Platform
Václav Chudáček, Lukás Zach, Jakub Kuzilek, Jirí Spilka, Lenka Lhotská

Data Driven Approach to ECG Signal Quality Assessment using Multistep SVM Classification
Jakub Kuzilek, Michal Huptych, Václav Chudáček, Jirí Spilka, Lenka Lhotská