ECG Signal Acquisition in .NET

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ECG Signal Acquisition
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One of the main problems in biometric signal processing is the high degree of noise and variations. In many cases, a reliable acquisition is only possible with suf cient knowledge of the spectral content, the dynamic range, and other characteristics not only of the desired signal components, but also of the noise sources involved. This is so that the appropriate lters and quantizers can be accordingly constructed to extract the desired signals, and reject the noise sources. The previous section has highlighted the salient characteristics of ECG signal components. For instance, the P wave is a lower-amplitude and lower-frequency signal, while the QRS complex exhibits a larger amplitude and higher frequency variations. In addition, the following sources of noise and artifacts are relevant to ECG. The baseline wander, arguably one of most common artifacts, refers to a low-frequency interference in the ECG, which may be induced by cardiovascular activities. The amplitude change due to baseline wander can potentially exceed the QRS amplitude by several times, which can be highly problematic for accurate medical diagnoses based on the isoelectric line. While this distortion may exhibit higher frequencies (e.g., during strenuous exercise), its spectral content is typically limited to an interval below 1 Hz [2]. Thus, some type of low-pass ltering would be relevant to this scenario.
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16.3 The ECG as a Biometric: A Literature Survey
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Another source of error is powerline interference, being 50 or 60 Hz depending on the geographical location, which occurs due to insuf cient grounding or interferences from other equipments. Also present in practical ECG recordings are electrode motion artifacts, due to skin stretching which alters the impedance around the electrode. These artifacts are problematic since their spectral content, being 1 10 Hz, overlaps that of the desired signal components. As well, there are inherent physiologically induced artifacts, namely, respiratory activity artifacts. The involved chest movements change the position of the heart and the lung conductivity, leading to not only variations in the heart rate, but also modi cations of the beat morphology [2]. Clearly, as in medical applications, an ECG-based biometric system needs to take into account all these various sources of error, using the appropriate preprocessing for example, ltering based on the speci c spectral contents.
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The ECG in Medical Settings
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Even though the SA node is the primary pacemaker of the heart, depolarization can also be initiated by other areas with pacemaker potential for example, by the autonomic foci: the atrial, junctional, and ventrical foci. But in such cases, the ECG may deviate from its normal healthy forms. Other conduction abnormalities may also cause disorders. For all these pathological conditions, collectively known as arrhythmias, the heart rhythms can become highly abnormal. Several kinds of arrhythmias can be classi ed in ECG monitoring. The most commonly encountered types are the premature heart beats. These beats are not generated by the SA node, but by other cardiac cells. Depending on their origin, the geometrical characteristics of the resulting waveforms may or may not be altered. In addition, the presence of the P wave is ambiguous. Two common types of premature beats are the atrial premature contraction (APC) and the premature ventricular contraction (PVC). When multiple focal points within the atria are responsible for an impulse, atrial arrhythmias are observed. Atrial tachycardia and atrial utter are some examples of this class of arrhythmias. For these arrhythmias, an abnormal or absent P wave is found in the recorded ECG, revealing the location of the ectopic focus. Arrhythmias originating in the ventricles are fatal rhythm disturbances that require immediate medical assistance, since they lead to cardiac arrest. Examples of these arrhythmias are the ventricular tachycardia, ventricular brillation, and ventricular utter. In the worst case, the ventricles produce several electrical signals at such a rapid rate that the rest of the heart s mechanism cannot follow.
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