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Post processing of raw data recorded with an ECG-vest

Aardal, Øyvind
Master thesis
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Aardal_master.pdf (5.205Mb)
Year
2008
Permanent link
http://urn.nb.no/URN:NBN:no-21234

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  • Anvendt matematikk og og mekanikk [229]
Abstract
Ischemic heart disease is the single most frequent cause of death in

the world today. Electrocardiogram (ECG) exercise testing is a common

tool for diagnosing this disease. With the ECG exercise test one can

compare the recording of the electrical activity in the heart during

exercise and rest. A shift between the rest and exercise recording in

the segment of the heartbeat called the ST segment is used both for

diagnosing ischemia, and as input to cardiac computation methods.

Body surface potential mappings (BSPM) are ECG recordings at a greater

number of locations on the torso, and provides better detection and

localisation properties than the traditional 12-lead ECG. In BSPM and ECG,

noise and drift from various sources are recorded in addition to the

signal propagating from the heart. A model for this is:

BSPM=signal+noise+drift.

Before accurate measurements of the ST segments in a BSPM

can be made, the noise and drift in the recording must be reduced

while keeping the signal unchanged. In this thesis, an automatic

algorithm for post processing raw BSPM data recordings was made.

The following methods have

been developed, implemented and tested as part of the algorithm:

First, noise reduction methods using frequency based filtering

techniques was implemented and tested. Second, an algorithm for

detecting the BSPM signal peaks was developed. This method was used to

locate the interesting parts of each heartbeat.

Third, methods for removing

the baseline drift is discussed. Four methods were selected,

implemented and evaluated against each other. A method using cubic

spline interpolation as an approximation to the drift was deemed

best and used in the automatic algorithm. Even after this initial

processing, there may be noisy or corrupted signal parts present in a

BSPM. Hence a framework for removing such parts of the BSPM was

developed as the fourth step of the algorithm. In the fifth step, a

robust method for computing the ST segment shifts at each electrode

location from a processed

BSPM was made. Finally, a tool for visualising these shifts was

created.

The algorithm developed in this thesis was applied to BSPM recordings

of real patients. Before processing, it was not possible to compute

neither reliable nor correct ST shifts from these recordings. After

the automatic algorithm was applied to these recordings, all the

resulting BSPMs were physically realistic, and showed signs of being

close to the true values. The computed ST shifts from the processed

data showed promising results for diagnosing ischemia in the limited

set of BSPMs available. In addition, a comparison between traditional

ECG and BSPM was made.
 
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