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Off-line ECG signal analysis

under MATLAB

What is g.ECGtoolbox for g.BSanalyze?

g.ECGtoolbox is a software package for ECG data processing and analysis. — The investigation of patterns and signal features of ECGs allows to observe noninvasively brain and heart functions and disfunctions.

The graphical user interface for g.ECGtoolbox enables you to investigate all important time and frequency domain features of your electrocardiogram (ECG) data such as RR intervals or HRV maps. You can load and save your preferred processing steps as a script program and automatically process your data in batch mode.

The g.ECGtoolbox can be ordered in two parts:

g.ECGtoolbox part I: HR and HRV analysis in time and frequency domain

g.ECGtoolbox part II: Single beat classification and analysis

NEW Toolbox Highlights

General
Frequency domain:
Robust QRS complex detection
Overlayed QRS detection result with raw ECG
Edit and manipulate QRS detection result
Recording reports
Power spectral density of resampled tachogram
Absolute measures of spectral power distribution (ULF, VLF, LF, HF)
Relative measures of spectral power distribution (LFnorm, HFnorm, LF/HF)
Time Domain:
Time-Frequency Evolution of HRV:
 HRV time-frequency maps
Tachogram , Resampled tachogram, histogram of RR intervals
Time domain measures and statistics: MeanRR, MeanHR, MaxRR, MinRR, MinMaxRRDiff,SDNN, SDHR
Segemented measures: SDANN, SDNNindex
RR difference measures: RMSSD, SDSD, NN50, pNN50
Geometric measures: HRVindex
Single beat classification and analysis:
Single beat editor
Automatic beat-by-beat detection of characteristic points: Pon, P, Poff, QRSon, Q, R, S, QRSoff, Ton, T, Toff
Time evolution plots for parameters
QT-interval and ST-segment analysis for identification of pathological changes
Classification of single beats

Part I: HR and HRV analysis in time and frequency domain

QRS complex detection

Starting from noisy raw ECG data, QRS complexes are automatically detected and indicated in the data editor with attribute QRS. An intelligent algorithm assigns the attribute QRSBAD to R-peaks that are not detected securely. These markers can now be corrected visually or (if necessary) excluded from further analyses. Time courses of tachogram and RR-intervals can also be displayed for visual inspection.

Time Domain ECG Features

 Time domain measures such as the evolution of the mean RR intervals NN50, the number of RR intervals differing by more than 50 ms, ...
Segmented Measures such as SDANN, the standard deviation of the averages of RR intervals in all segments of the recording, ...
Geometric Measures such as HRVindex yielding the total number of RR intervals divided by the number of RR intervals, ...

Frequency Domain ECG Features

ECG data analysis in the frequency domain allows you to investigate heart rate variability oscillations at different frequencies. These oscillations are originated by different physiological systems. The parasympathetic and sympathetic systems modulate the heart rate variability. High frequency oscillations (about 0.2-0.35 Hz) are vagally mediated and low frequency oscillations (around 0.1 Hz) are due to both parasympathetic and sympathetic systems. The respiratory sinus arrhythmia (RSA) is vagally mediated and has a frequency synchronous to the respiratory cycle (between 0.2 and 0.35 Hz). Very low frequency components are associated with slow regulation mechanisms such as humoral and thermoregulation factors.

 

 Absolute Measures such as the 4 main spectral components (ULF, VLF, LF, HF) are extracted from a calculated spectrum, ...
Relative Measures such as the ratio of LF/HF or LF normalized by the total power TP, ...

Time-Frequency ECG Analysis

Example: HRV maps

To simplify the data analysis and interpretation of the ECG data HRV maps allow to estimate the PSD (power spectral density) for a certain segment. Then the segment is shifted by a specific stepsize and the PSD is calculated again. This yields a comprehensive time-frequency analysis plot over the recording time. High power values are indicated in red, low power values are shown in blue.

In addition to the time frequency plot, the time course of the spectral components ULF, LF, HF, VHF are also displayed in the protocol.

 

Part II: Single beat classification and analysis

 
in cooperation with:
Division: Biosignal Processing and Telemonitoring
Single Beat Editor

The single beat editor is an intelligent and very convenient tool displaying single ECG beats and measuring characteristic points in the ECG signals. QT-, ST-intervals as well as time instants of Pon, P, Poff, QRSon, Q, R, S, QRSoff, Ton, T, Toff are determined. The detector was developed using thousands of ECG recordings and is able to deal with irregular heart rhythms, an arbitrary number of channels and arbitrary sampling frequencies (winner of the Computers in Cardiology Challange 2001 and 2004).
In addition different classes of beats can be displayed: Normal beats or non-normal beats (extrasystols with classification of the type)

Example 1: QT-, ST- intervals and QRS amplitudes

Characteristic intervals and ECG signal features can be displayed as function of time. The example to the right resembles the amplitude changes in QRS (color black), QT-interval (color red) and ST-interval (color blue) changes for a tilt table experiment. The subject was laying in horizontal position on a tilt table till second 1000. Then the table was tilted by 90 degrees.
The QT-interval is an important parameter concerning the repolarization process. Prolonged QT, for example, increases the risk of ventricular arrhythmias. The QRS amplitude and duration is offering information about the depolarization of the heart and is used for detection of abnormal interventricular conduction, coronary heart disease, pericardial effusion etc. ST-segment changes provide information for detection of ischemia and infarct.
Example 2: QRS complex classification


Each QRS complex can be classified according to the underlying ventricular rhythm and the morphology of the averaged heart beat.

Each heart beat is classified into one of the following QRS types:
  • Normal - Normal heart beat (i.e. no pathology detected)

  • Complete BBB - Complete bundle branch block

  • Incomplete BBB - Incomplete bundle branch block

  • Ventricular ectopic - Ventricular ectopic beat. Premature beat with origin somewhere in the ventricular myocardium

  • Supraventricular ectopic - Supraventricular ectopic beat. Premature beat with origin in the Sinus node, atrium or in the fast conducting system of the ventricles (e.g. AV node, bundle of HIS, bundle branches etc.)

 

The results of the classification are summarized in the Signal Summery report. The report contains information about the processed data set, the number of QRS complexes per identified QRS type and timing information of the QRS waves.

User Story - Find the beats of interest

WINNER of the CinC Challenge 2006

Download brochure: ECG-Toolbox (PDF 1.5 MByte)

Download complete brochure: g.BSanalyze (PDF 5.7 MByte)
 

Package includes Software modules, help manual, hardlock
Technical Requirements MATLAB, g.BSanalyze base version

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