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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ramos, J.A. Paul, J.S. |
| Copyright Year | 2003 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Purdue Sch. of Enginering & Technol., Indianapolis, IN, USA (Ramos, J.A.; Paul, J.S.) |
| Abstract | A major problem associated with longterm ECG recordings is the enormous volume of data they contain and the requirement of an efficient procedure for its archival in reduced form is highly desirable. The storage of multiple recordings poses limitations, especially when they are to be used at a later time for applications involving high resolution mode, such as the contextual analysis of ECG. This paper presents an application of the singular value decomposition (SVD) within a total least squares (TLS) framework for data reduction of longterm ECG recordings. We present a combined formulation of denoising and data reduction via a TLS approach. Following beat delineation, archival of the ECG beat is accomplished using the reduced parameter set obtained using the TLS approximation in the discrete cosine transform (DCT) domain. Casting the transform domain ECG signal into a structured form using only the significant DCT coefficients resulted in a substantial reduction of the computational complexity involved in estimating the model parameters. With the reduced parameter set obtained using the proposed TLS approach, it was possible to archive multiple recordings of ambulatory Holter ECG data in a personal computer with only a limited storage capacity. |
| Sponsorship | Honeywell Lab. Xerox Nat. Instruments Math Works |
| Starting Page | 6435 |
| Ending Page | 6440 |
| File Size | 336391 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780379241 |
| ISSN | 01912216 |
| DOI | 10.1109/CDC.2003.1272359 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-12-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Least squares methods Electrocardiography Discrete cosine transforms Singular value decomposition Noise reduction Least squares approximation Casting Discrete transforms Computational complexity Parameter estimation |
| Content Type | Text |
| Resource Type | Article |
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