Title :
Applications of rank-reduction to ECG analysis
Author :
Semnani, RJ ; Womack, BF ; Diller, KR
Author_Institution :
Dept. of Electr. & Biomed. Eng., Texas Univ., Austin, TX, USA
Abstract :
The authors demonstrate application of SVD-based subspace techniques to electrocardiography. SVD, a high resolution spectrum estimation tool, is used to decompose the ECG data matrix into orthogonal subspaces. Due to the energy-preserving orthogonal transformations in the SVD, these subspaces correspond to the signal and noise components contained in the ECG data. Projection of the data onto the desired subspace eliminates the noise and the unwanted signal components
Keywords :
electrocardiography; medical signal processing; singular value decomposition; spectral analysis; ECG analysis; ECG data matrix decomposition; SVD-based subspace techniques; data projection; electrodiagnostics; energy-preserving orthogonal transformations; high resolution spectrum estimation tool; noise components; orthogonal subspaces; rank-reduction applications; signal components; unwanted signal components; Biomedical engineering; Distortion; Electrocardiography; Energy resolution; Event detection; Matrix decomposition; Monitoring; Signal processing; Signal resolution; Spectral analysis;
Conference_Titel :
Computers in Cardiology 1998
Conference_Location :
Cleveland, OH
Print_ISBN :
0-7803-5200-9
DOI :
10.1109/CIC.1998.731714
