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Abstract Background In equine medicine, 12‐lead electrocardiograms (ECGs) rarely are used, which may in part be a result of shortcomings in the existing guidelines for obtaining 12‐lead ECGs in horses. The guidelines recommend placing the limb leads on the extremities, which is inappropriate because the ventricular mean electrical axis is then perpendicular to the limb leads, leading to large variations in ECG configuration even among healthy horses. From an electrophysiological point of view, the leads instead should be parallel to the electrical axis to minimize variability. Objective Develop an improved method for obtaining 12‐lead ECGs in horses based on electrophysiology and cardiac electrical vectors relevant to horses. Animals Thirty‐five healthy Standardbred horses. Methods Two ECGs obtained at rest; 1 ECG with the electrodes placed according to the method developed in the present study, the Copenhagen method, and 1 ECG following existing guidelines. Results In the Copenhagen method, we repositioned the limb electrodes to the thorax to better capture the electrical activity of the heart. Variation in the mean electrical axis decreased dramatically with the Copenhagen method (SD decreased from 24.6° to 1.6°, P

Background: In equine medicine, 12‐lead electrocardiograms (ECGs) rarely are used, which may in part be a result of shortcomings in the existing guidelines for obtaining 12‐lead ECGs in horses. The guidelines recommend placing the limb leads on the extremities, which is inappropriate because the ventricular mean electrical axis is then perpendicular to the limb leads, leading to large variations in ECG configuration even among healthy horses. From an electrophysiological point of view, the leads instead should be parallel to the electrical axis to minimize variability. Objective: Develop an improved method for obtaining 12‐lead ECGs in horses based on electrophysiology and cardiac electrical vectors relevant to horses. Animals Thirty‐five healthy Standardbred horses. Methods: Two ECGs obtained at rest; 1 ECG with the electrodes placed according to the method developed in the present study, the Copenhagen method, and 1 ECG following existing guidelines. Results: In the Copenhagen method, we repositioned the limb electrodes to the thorax to better capture the electrical activity of the heart. Variation in the mean electrical axis decreased dramatically with the Copenhagen method (SD decreased from 24.6° to 1.6°, P <.001). Consequently, this new method provided stable ECGs with repeatable configurations. Conclusions and Clinical Importance: With this novel method, the ECG is recorded with respect to the electric axis to fully realize the potential of 12‐lead ECG in horses. The Copenhagen method delivered more consistent and reliable ECG recordings compared to existing guidelines. The Copenhagen method potentially allows for expanded use of 12‐lead ECGs in equine medicine. [ABSTRACT FROM AUTHOR]

With the development of society, health has attracted more and more attention. Heart disease is a common and frequently occurring disease, and it is fatal. Rapid and timely diagnosis and treatment of heart disease is very important. Electrocardiogram (ECG) reflects human heart health and is widely used in heart disease examination. Existing methods depending on doctors' personal experience and diagnostic level are time-consuming and inefficient. Therefore, a classification method that can automatically analyze ECG is required. Aiming at the classification of 12-lead ECG, based on the good performance of convolution neural network, this paper proposes a method of ECG classification based on lead convolution neural network, which can effectively and accurately detect, recognize and classify ECG. First, the image features are extracted after the ECG is preprocessed, and then using the fuzzy set reduces the extracted ECG image features. Then, residual learning is used to optimize the convolutional neural network, and in order to ensure that the network is easy to train and fast convergence, a random parameter initialization method is introduced to achieve better classification results. The simulation results show that the proposed multi-lead filtering algorithm reduces the loss of useful information while eliminating noise; at the same time, the convolution neural network can effectively and accurately classify ECG images; and the introduction of residual network can improve the classification effect. [ABSTRACT FROM AUTHOR]

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Importance AliveCor ECG is an FDA approved ambulatory cardiac rhythm monitor that records a single channel (lead I) ECG rhythm strip using an iPhone. In the past few years, the use of smartphones and tablets with health related applications has significantly proliferated. Objective In this initial feasibility trial, we attempted to reproduce the 12 lead ECG using the bipolar arrangement of the AliveCor monitor coupled to smart phone technology. Methods We used the AliveCor heart monitor coupled with an iPhone cellular phone and the AliveECG application (APP) in 5 individuals. Results In our 5 individuals, recordings from both a standard 12 lead ECG and the AliveCor generated 12 lead ECG had the same interpretation. Conclusions This study demonstrates the feasibility of creating a 12 lead ECG with a smart phone. The validity of the recordings would seem to suggest that this technology could become an important useful tool for clinical use. This new hand held smart phone 12 lead ECG recorder needs further development and validation. [ABSTRACT FROM AUTHOR]