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:
Toolbox Highlights
General
- Robust QRS complex detection
- Overlayed QRS detection result with raw ECG
- Edit and manipulate QRS detection result
- Recording reports
Time domain
- 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
Frequency domain
- 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-Frequency Evolution of HRV
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
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.
Package includes
- Software modules
- help manual
- hardlock
Technical Requirements
MATLAB, g.BSanalyze base version
Copyright © g.tec |
)
)
)
)
)
)
)
)