Show simple item record

dc.contributor.advisorKöymen, Hayrettinen_US
dc.contributor.authorAcar, Buraken_US
dc.date.accessioned2016-01-08T20:13:20Z
dc.date.available2016-01-08T20:13:20Z
dc.date.issued1996
dc.identifier.urihttp://hdl.handle.net/11693/17777
dc.descriptionAnkara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1996.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 1996.en_US
dc.descriptionIncludes bibliographical references leaves 69-70.en_US
dc.description.abstractElectrocardiogram (ECG) is the measurement of potential differences occurring on the body due to the currents that flow on the heart during diastole and systole. Cardiac abnormalities cause uncommon current flows, leading to strange waveform morphologies in the recorded ECG. Since some abnormalities become visible in ECG only during activity, exercise ECG tests are conducted. The sources of noise during an exercise test are electro myogram (EMG) due to increased muscle activity and baseline wander (BW) due to mechanical motion. Frequency band filtering, used to eliminate noise, is not an efficient method for filtering noise because usually frequency spectra of the interference and the ECG overlap. Rather, a fast morphological filter is required. This thesis is focused on an online filtering approach which separates noise and ECG signals without changing the morphology. The redundancy present in standard 12 lead ECG records is made operational by a Singular Value Decomposition based orthogonalization of the input signals. ECG is represented in a minimum dimensional space whose orthogonal complement takes on noise. The signals in this low dimensional space are used to reconstruct the input signals without noise. Noise elimination also improves data compression. A comparative study of the ST analysis of original and reconstructed signals is presented at the end.en_US
dc.description.statementofresponsibilityAcar, Buraken_US
dc.format.extentix, 70 leavesen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectExercise ECGen_US
dc.subjectSingular Value Decomposition (SVD)en_US
dc.subjectOnline Orthogonalizationen_US
dc.subjectOnline Filteringen_US
dc.subject.lccQP112.5.E4 A33 1996en_US
dc.subject.lcshElectrocardiography.en_US
dc.subject.lcshElectrocardiography--Mathematical models.en_US
dc.subject.lcshBiological control systems--Data processing.en_US
dc.subject.lcshSignal processing--Digital techniques.en_US
dc.subject.lcshElectric filters, Digital.en_US
dc.subject.lcshElectrocardiography--Data processing.en_US
dc.titleOnline ECG signal orthogonalization based on singular value decompositionen_US
dc.typeThesisen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record