Title :
Design for an artificial neural network system to obtain 12-lead ECG from 3-lead Holter VCG recordings
Author :
Kuppuraj, Ravi Narayan ; Napper, Stan
Author_Institution :
Dept. of Biomed. Eng., Louisiana Tech. Univ., Ruston, LA, USA
Abstract :
Cardiac experts often make critical diagnoses utilizing information from the standard 12-lead ECG rather than Holter recordings. The development of a Neural Network (NN) system to derive the 12-lead ECG from modified VCG leads recorded using Holter recordings is explored here. The requirements (data acquisition, hardware, software, etc.) of such a system are addressed. A NN to derive the 12-lead ECG with the 3-lead modified VCG as its input is designed
Keywords :
electrocardiography; 12-lead ECG; 3-lead Holter VCG recordings; artificial neural network system design; cardiac experts; critical diagnoses; data acquisition; Artificial neural networks; Backpropagation; Data acquisition; Electrocardiography; Frequency; Hardware; Monitoring; Neural networks; Packaging; Rhythm;
Conference_Titel :
Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-2050-6
DOI :
10.1109/IEMBS.1994.415351
