The details of digital recording and computer processing of a 12-lead electrocardiogram (ECG) remain a source of confusion for many health care professionals. A better understanding of the design and performance tradeoffs inherent in the electrocardiograph design might lead to better quality in ECG recording and better interpretation in ECG reading. This paper serves as a tutorial from an engineering point of view to those who are new to the field of ECG and to those clinicians who want to gain a better understanding of the engineering tradeoffs involved. The problem arises when the benefit of various electrocardiograph features is widely understood while the cost or the tradeoffs are not equally well understood. An electrocardiograph is divided into 2 main components, the patient module for ECG signal acquisition and the remainder for ECG processing which holds the main processor, fast printer, and display. The low-level ECG signal from the body is amplified and converted to a digital signal for further computer processing. The Electrocardiogram is processed for display by user selectable filters to reduce various artifacts. A high-pass filter is used to attenuate the very low frequency baseline sway or wander. A low-pass filter attenuates the high-frequency muscle artifact and a notch filter attenuates interference from alternating current power. Although the target artifact is reduced in each case, the ECG signal is also distorted slightly by the applied filter. The low-pass filter attenuates high-frequency components of the ECG such as sharp R waves and a high-pass filter can cause ST segment distortion for instance. Good skin preparation and electrode placement reduce artifacts to eliminate the need for common usage of these filters.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jelectrocard.2007.08.059 | DOI Listing |
Digit Health
January 2025
Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: Although the evaluation of left ventricular ejection fraction (LVEF) in patients with atrial fibrillation (AF) or atrial flutter (AFL) is crucial for appropriate medical management, the prediction of reduced LVEF (<50%) with AF/AFL electrocardiograms (ECGs) lacks evidence. This study aimed to investigate deep-learning approaches to predict reduced LVEF (<50%) in patients with AF/AFL ECGs and easily obtainable clinical information.
Methods: Patients with 12-lead ECGs of AF/AFL and echocardiography were divided into those with LVEF <50% and ≥50%.
Eur Heart J Case Rep
January 2025
Cardiology Department, Loyola University Medical Center, 2160 S 1st Ave, Maywood, IL 60153-3328, USA.
Background: Immune checkpoint inhibitors (ICIs) are effective antineoplastic agents but can cause adverse effects in many organ systems. Cardiovascular toxicities include arrhythmias, myocarditis, heart failure, takotsubo syndrome, pericarditis, coronary artery disease, and vasculitis.
Case Summary: A 66-year-old woman with Stage 3C2 endometrial carcinoma presented for her second cycle of pembrolizumab, carboplatin, and paclitaxel.
ACS Sens
January 2025
Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, Missouri 65409, United States.
Wearable sensors are increasingly being used as biosensors for health monitoring. Current wearable devices are large, heavy, invasive, skin irritants, or not continuous. Miniaturization was chosen to address these issues, using a femtosecond laser-conversion technique to fabricate miniaturized laser-induced graphene (LIG) sensor arrays on and encapsulated within a polyimide substrate.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Department of Biomedical Engineering, National Defense Medical Center, Taiwan, No.161, Sec.6, Minchiuan E. Rd., Neihu Dist, Taipei, 11490, Taiwan.
Background: As the incidence and prevalence of Atrial Fibrillation (AF) proliferate worldwide, the condition has become the epicenter of a plethora of ECG diagnostic research. In recent diagnostic methodologies, Morse Continuous Wavelet Transform (MsCWT) is a feature extraction technique utilized to draw out distinctive attributes of ECG signals. In our study, we explore the employment of MsCWT in the classification of AF with ECG signals in a continuum.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Department of Cardiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Introduction: The risk of mortality associated with cardiac arrhythmias is considerable, and their diagnosis presents significant challenges, often resulting in misdiagnosis. This situation highlights the necessity for an automated, efficient, and real-time detection method aimed at enhancing diagnostic accuracy and improving patient outcomes.
Methods: The present study is centered on the development of a portable deep learning model for the detection of arrhythmias via electrocardiogram (ECG) signals, referred to as CardioAttentionNet (CANet).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!