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๑۩۞۩๑ سایت جامع مهندسی پزشکی ایران ๑۩۞۩๑ - LabVIEW for ECG Signal Processing

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LabVIEW for ECG Signal Processing

پنجشنبه 9 خرداد 1387   02:05 ق.ظ


نوع مطلب : سیگنال های قلبی ،

LabVIEW for ECG Signal Processing

  1. Preprocessing ECG Signals
  2. Performing Feature Extraction on ECG Signals
  3. Summary

The electrocardiogram (ECG) is a technique of recording bioelectric currents generated by the heart. Clinicians can evaluate the conditions of a patient's heart from the ECG and perform further diagnosis. ECG records are obtained by sampling the bioelectric currents sensed by several electrodes, known as leads. A typical one-cycle ECG tracing is shown in Figure 1.


Figure 1: A typical one-cycle ECG tracing

Generally, the recorded ECG signal is often contaminated by noise and artifacts that can be within the frequency band of interest and manifest with similar characteristics as the ECG signal itself. In order to extract useful information from the noisy ECG signals, you need to process the raw ECG signals.

ECG signal processing can be roughly divided into two stages by functionality: preprocessing and feature extraction (as shown in Figure 2). The preprocessing stage removes or suppresses noise from the raw ECG signal and the feature extraction stage extracts diagnostic information from the ECG signal.

Figure 2: Typical ECG signal processing flowchart

With LabVIEW and related toolkits, such as the Advanced Signal Processing Toolkit (ASPT) and the Digital Filter Design Toolkit (DFDT), you can conveniently build signal processing applications for both stages, including baseline wandering removing, noise cancellation, QRS complexes detection, fetal heart rate extraction and etc. This article discusses typical ECG signal processing methods based on LabVIEW.

Preprocessing ECG Signals

Preprocessing ECG signals helps you remove contaminants from the ECG signals. Broadly speaking, ECG contaminants can be classified into the following categories:

  • power line interference
  • electrode pop or contact noise
  • patient–electrode motion artifacts
  • electromyographic (EMG) noise
  • baseline wandering

Among these noises, the power line interference and the baseline wandering are the most significant and can strongly affect ECG signal analysis. Except for these two noises, other noises may be wideband and usually a complex stochastic process which also distort the ECG signal. The power line interference is narrow-band noise centered at 60 Hz (or 50 Hz) with a bandwidth of less than 1 Hz. Usually the ECG signal acquisition hardware can remove the power line interference. However the baseline wandering and other wideband noises are not easy to be suppressed by hardware equipments. Instead, the software scheme is more powerful and feasible for offline ECG signal processing. You can use the following methods to remove baseline wandering and the other wideband noise.

Removing Baseline Wandering

Baseline wandering usually comes from respiration at frequencies wandering between 0.15 and 0.3 Hz, and you can suppress it by a highpass digital filter. You also can use the wavelet transform to remove baseline wandering by eliminating the trend of the ECG signal.

1. Digital Filter Approach

The LabVIEW DFDT provides an intuitive and interactive way to design and implement finite impulse response (FIR) or infinite impulse response (IIR) filters easily and effectively. For example, you can use the Classical Filter Design Express VI to design a Kaiser Window FIR highpass filter to remove the baseline wandering. Figure 3 shows an example of the specifications of the highpass filter and the block diagram of a sample VI that you can use to remove the baseline wandering.

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نوشته شده توسط : سایت جامع مهندسی پزشکی