Title :
A neural network approach to electrical impedance cardiography
Author :
Kumar, Amaresh A R ; Taylor, Bruce C. ; Mulavara, Ajitkumar P. ; Nair, Meera S. ; Gupta, Vineet ; Timmons, William D.
Author_Institution :
Dept. of Biomed. Eng., Akron Univ., OH, USA
Abstract :
A novel technique to determine cardiac stroke volume using electrical impedance variables is presented. Recent studies have shown that stroke volumes calculated using Kubicek and Sramek impedance equations correlate poorly with Doppler ultrasound (R=0.34). However, by applying a neural network to these same impedance variables, we demonstrated greatly improved correlation (R=0.87) and predictability. This non-linear black box approach to impedance cardiography may lead to a more reliable and inexpensive method for the noninvasive measurement of stroke volume and cardiac output
Keywords :
cardiology; Doppler ultrasound; cardiac output; cardiac stroke volume; correlation; electrical impedance cardiography; electrical impedance variables; impedance equations; neural network approach; noninvasive measurement; nonlinear black box approach; predictability; Biomedical engineering; Cardiography; Cardiology; Electrodes; Equations; Impedance measurement; Neural networks; Testing; Thorax; Ultrasonic imaging;
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.1994.415320
