Abstract
BackgroundFast and accurate quality estimation of the electrocardiogram (ECG) signal is a relevant research topic that has attracted considerable interest in the scientific community, particularly due to its impact on tele-medicine monitoring systems, where the ECG is collected by untrained technicians. In recent years, a number of studies have addressed this topic, showing poor performance in discriminating between clinically acceptable and unacceptable ECG records.Methods This paper presents a novel, simple and accurate algorithm to estimate the quality of the 12-lead ECG by exploiting the structure of the cross-covariance matrix among different leads. Ideally, ECG signals from different leads should be highly correlated since they capture the same electrical activation process of the heart. However, in the presence of noise or artifacts the covariance among these signals will be affected. Eigenvalues of the ECG signals covariance matrix are fed into three different supervised binary classifiers.Results and conclusion The performance of these classifiers were evaluated using PhysioNet/CinC Challenge 2011 data. Our best quality classifier achieved an accuracy of 0.898 in the test set, while having a complexity well below the results of contestants who participated in the Challenge, thus making it suitable for implementation in current cellular devices.
Highlights
Fast and accurate quality estimation of the electrocardiogram (ECG) sig‐ nal is a relevant research topic that has attracted considerable interest in the scientific community, due to its impact on tele-medicine monitoring systems, where the ECG is collected by untrained technicians
The objective of this work is to provide a novel technique to classify the quality of the ECG signal based on the covariance matrix of the leads using a simple and computationally low-cost algorithm
The behavior of the proposed classifiers has been analyzed by using the Dataset A, since this is the only data that provide both the ECG signals and their corresponding labels (AC, UN)
Summary
Fast and accurate quality estimation of the electrocardiogram (ECG) sig‐ nal is a relevant research topic that has attracted considerable interest in the scientific community, due to its impact on tele-medicine monitoring systems, where the ECG is collected by untrained technicians. Automatic estimation of ECG quality is of paramount importance, in tele-monitoring applications where the ECG is commonly collected by untrained or inexperienced technicians; or even self-monitoring applications, where. Tele-ECG applications will make a difference in developing countries lacking adequate primary care capacity. In such scenarios, automatic real-time assessment of ECG quality is required in order to alert the technician about the need to repeat the ECG while the patient is still present. Automatic real-time assessment of ECG quality is required in order to alert the technician about the need to repeat the ECG while the patient is still present This task could be performed by current cellular terminals (smartphones) able to capture and to instantaneously estimate the quality of the ECG [2]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
