KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Physical Science and Engineering (PSE) Division
Sensing, Magnetism and Microsystems Lab
Permanent link to this recordhttp://hdl.handle.net/10754/564372
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AbstractThe Electrocardiography (ECG) is a tool measuring the electrical excitation of the heart that is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological processes. The respiratory activity is a prominent process that affects the ECG signal due to the close proximity of the heart and the lungs and, on the other hand, due to neural regulatory processes. In this paper, several means for the estimation of the respiratory process from the ECG signal are presented. The results show a strong correlation of the voltage difference between the R and S peak of the ECG and the lung's volume and pressure. Correlation was also found for some features of the vector ECG, which is a two dimensional graph of two different ECG signals. The potential benefit of the multiparametric evaluation of the ECG signal is a reduction of the number of sensors connected to patients, which will increase the patients' comfort and reduce the costs associated with healthcare. In particular, it is relevant for sleep monitoring, where a reduction of the number of different sensors would facilitate a more natural sleeping environment and hence a higher sensitivity of the diagnosis. © 2011 IEEE.
Conference/Event name2011 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2011