ECG parametric modeling based on signal dependent orthogonal transform
In this letter, we propose a parametric modeling technique for the electrocardiogram (ECG) signal based on signal dependent orthogonal transform. The technique involves the mapping of the ECG heartbeats into the singular values (SV) domain using the left singular vectors matrix of the impulse respon...
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| Format: | Article |
| Language: | English |
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IEEE
2014
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| Online Access: | http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/1/06847763_SPL.pdf |
| _version_ | 1848781363437633536 |
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| author | Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim |
| author_facet | Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim |
| author_sort | Baali, Hamza |
| building | IIUM Repository |
| collection | Online Access |
| description | In this letter, we propose a parametric modeling technique for the electrocardiogram (ECG) signal based on signal dependent orthogonal transform. The technique involves the mapping of the ECG heartbeats into the singular values (SV) domain using the left singular vectors matrix of the impulse response matrix of the LPC filter. The resulting spectral coefficients vector would be concentrated, leading to an approximation to a sum of exponentially damped sinusoids (EDS). A two-stage procedure is then used to estimate the model parameters. The Prony’s method is first employed to obtain initial estimates of the model, while the Levenberg–Marquardt (LM) method is then applied to solve the non-linear least-square optimization problem. The ECG signal is
reconstructed using the EDS parameters and the linear prediction coefficients via the inverse transform. The merit of the proposed modeling technique is illustrated on the clinical data collected from the MIT-BIH database including all the arrhythmias classes that are recommended by the Association for the Advancement of Medical Instrumentation (AAMI). For all the tested ECG heartbeats, the average values of the percent root mean square difference (PRDs) between the actual and the reconstructed signals were relatively low, varying between a minimum of 3.1545% for
Premature Ventricular Contractions (PVC) class and a maximum
of 10.8152% for Nodal Escape (NE) class. |
| first_indexed | 2025-11-14T15:48:22Z |
| format | Article |
| id | iium-37155 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:48:22Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-371552018-05-24T07:55:28Z http://irep.iium.edu.my/37155/ ECG parametric modeling based on signal dependent orthogonal transform Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim TK Electrical engineering. Electronics Nuclear engineering In this letter, we propose a parametric modeling technique for the electrocardiogram (ECG) signal based on signal dependent orthogonal transform. The technique involves the mapping of the ECG heartbeats into the singular values (SV) domain using the left singular vectors matrix of the impulse response matrix of the LPC filter. The resulting spectral coefficients vector would be concentrated, leading to an approximation to a sum of exponentially damped sinusoids (EDS). A two-stage procedure is then used to estimate the model parameters. The Prony’s method is first employed to obtain initial estimates of the model, while the Levenberg–Marquardt (LM) method is then applied to solve the non-linear least-square optimization problem. The ECG signal is reconstructed using the EDS parameters and the linear prediction coefficients via the inverse transform. The merit of the proposed modeling technique is illustrated on the clinical data collected from the MIT-BIH database including all the arrhythmias classes that are recommended by the Association for the Advancement of Medical Instrumentation (AAMI). For all the tested ECG heartbeats, the average values of the percent root mean square difference (PRDs) between the actual and the reconstructed signals were relatively low, varying between a minimum of 3.1545% for Premature Ventricular Contractions (PVC) class and a maximum of 10.8152% for Nodal Escape (NE) class. IEEE 2014-10 Article PeerReviewed application/pdf en http://irep.iium.edu.my/37155/1/06847763_SPL.pdf Baali, Hamza and Akmeliawati, Rini and Salami, Momoh Jimoh Eyiomika and Khorshidtalab, Aida and E., Lim (2014) ECG parametric modeling based on signal dependent orthogonal transform. IEEE Signal Processing Letters, 21 (10). pp. 1293-1297. ISSN 1070-9908 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6847763 10.1109/LSP.2014.2332425 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim ECG parametric modeling based on signal dependent orthogonal transform |
| title | ECG parametric modeling based on signal dependent orthogonal transform |
| title_full | ECG parametric modeling based on signal dependent orthogonal transform |
| title_fullStr | ECG parametric modeling based on signal dependent orthogonal transform |
| title_full_unstemmed | ECG parametric modeling based on signal dependent orthogonal transform |
| title_short | ECG parametric modeling based on signal dependent orthogonal transform |
| title_sort | ecg parametric modeling based on signal dependent orthogonal transform |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/1/06847763_SPL.pdf |