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Baseline Suppression in ECG-signals. Lisette Harting. Contents. Introduction to the problem Problem approach ECG analysis Common used solutions & ideas Results Conclusions and recommendations Questions. contents - introduction - approach - ECG - literature - results - conclusions.
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Baseline Suppression in ECG-signals Lisette Harting
Contents • Introduction to the problem • Problem approach • ECG analysis • Common used solutions & ideas • Results • Conclusions and recommendations • Questions contents - introduction - approach - ECG - literature - results - conclusions
Introduction to the problem contents - introduction - approach - ECG - literature - results - conclusions
Function of the heart • Distribute oxygen and nutrition contents - introduction - approach - ECG - literature - results - conclusions
Pathology • Bad conductance of signal • Second pacer also initiates contraction • Needs to be destructed: destructor • 2 types of operation: • Open chest • Minimal surgery (catheters, ablation) contents - introduction - approach - ECG - literature - results - conclusions
Measuring ECG/EG • Where does the ECG origin? • Chest (only) resistive potentials on the skin ~ potentials on heart * factor • Three deductions of ECG contents - introduction - approach - ECG - literature - results - conclusions
Measuring ECG/EG • Extremity leads • Einthoven • Goldberger contents - introduction - approach - ECG - literature - results - conclusions
Measuring ECG/EG • Precordial leads contents - introduction - approach - ECG - literature - results - conclusions
Application • Diagnostic system • Exercise ECG • Operation room system contents - introduction - approach - ECG - literature - results - conclusions
Baseline drift • In exercise ECG caused by • Movements of the patient • Breathing • Changing electrode – skin contact • In operation room merely caused by • Breathing • Ablation contents - introduction - approach - ECG - literature - results - conclusions
Assignment • Design of baseline drift filter for operation-room ECG • With test-signals for breathing originated baseline drift • Later to be used in exercise ECG and other applications contents - introduction - approach - ECG - literature - results - conclusions
Specifications • Input: • Multiple channels (6 to > 12) • Already first order high pass-filtered with cutoff frequency 0.5 Hz or 0.05 Hz contents - introduction - approach - ECG - literature - results - conclusions
Desired output: • Cutoff frequency 0.5 Hz • 0.5 Hz and lower: minimal 6 dB attenuation • Delay maximal 120 ms • Minimize signal to noise ratio • Minimize distortion of signal • Must work real time on a normal computer contents - introduction - approach - ECG - literature - results - conclusions
Problem approach contents - introduction - approach - ECG - literature - results - conclusions
Work • Literature study • Oscillation filter on synthetic test signal • IIR / FIR • Analyzed experimental signals • Made for-backward filter with heart rate adaptation • Demonstration program contents - introduction - approach - ECG - literature - results - conclusions
To do: • Write report • Optimize chosen filter further • Work out theoretical problem • No time for: • Adaptive filters contents - introduction - approach - ECG - literature - results - conclusions
ECG-signal analysis contents - introduction - approach - ECG - literature - results - conclusions
Time domain contents - introduction - approach - ECG - literature - results - conclusions
PSD contents - introduction - approach - ECG - literature - results - conclusions
SNR • Signal to noise ratio (from PSD) • S/N = 10 * 10log(Ps/Pn) • Signal • Heart rate and higher frequencies • Noise • Rest of signal • Compared qualities of the signals from the 19 experiments contents - introduction - approach - ECG - literature - results - conclusions
Heartrate • Varied between 25 and 35 • Was detected correctly 100% by the algorithm (to be discussed later) • Not tested with ill patients contents - introduction - approach - ECG - literature - results - conclusions
Common solutions contents - introduction - approach - ECG - literature - results - conclusions
delay + - low pass filter Filters • Idea behind hp digital filters: • Out = In(delayed) – In(filtered) contents - introduction - approach - ECG - literature - results - conclusions
Average based filters • Average based filters • Moving average filters (box) • Triangular FIR-filter • With smart size of window to be able to use shifting instead of division after adding • FIR • May be linear phase • But need large calculation power contents - introduction - approach - ECG - literature - results - conclusions
Bidirectional filters • Input hardware filter is reversed in time and sampled • Symmetric filter (zero phase shift) • Problem: fixed cutoff frequency contents - introduction - approach - ECG - literature - results - conclusions
Incrementally changing filter • Incrementally changing filter for QRS-complex and rest of ECG-signal contents - introduction - approach - ECG - literature - results - conclusions
Slew rate limiter • slew rate limiter • Against fast increase of baseline drift (optimize step response) • Limit rising and falling rate of the signal contents - introduction - approach - ECG - literature - results - conclusions
Other solutions contents - introduction - approach - ECG - literature - results - conclusions
Heart rate detection • Simple algorithm: • Derivative < minimal value count+1 • Derivative > minimal value reset count • If count > limit QRS-complex detected • reset count • pause detection algorithm 100 ms • adjust cutoff frequency filter • Time between 2 complexes = heart rate contents - introduction - approach - ECG - literature - results - conclusions
Envelope method • Baseline drift estimation: • envelope around input signal • Estimation is mean of the envelope • Idea: • Use information about ECG phase • to correct for distortion of ECG • based on (measured) phase dependent distortion of a pure ECG-signal contents - introduction - approach - ECG - literature - results - conclusions
Adaptive oscillator • Principle: • Suppress ECG-signal (SLR or lp-filter) • After SLR-interval: average is BLD-estimation • Use 2 BLD-estimates to predict 3rd (IIR): • d(n) = a(n) * d(n-w) – d(n-2w) • Update ‘a’ • a(n+1) = a(n) + [d_real(n) – d_meas(n)] / d(n-1) contents - introduction - approach - ECG - literature - results - conclusions
Cross-Correlation filter • Principle • Do not adapt filters one by one, but use knowledge about other signals • Why? • There is a high correlation between the signals contents - introduction - approach - ECG - literature - results - conclusions
Cross-correlation filter • Why not? • Fast (10 s) and high (90%) changes of the correlation between the signals • Low frequencies need a lot of time & memory to calculate correlation • Non-linear relation between signals • Heart rate would need to be filtered out too contents - introduction - approach - ECG - literature - results - conclusions
For-backward filtering • Principle • Minimize calculation time • decimation • IIR-filtering • Linearize and increase steepness IIR-filter by filtering also backward contents - introduction - approach - ECG - literature - results - conclusions
For-backward filtering • Working: • Prefilter signal with cutoff freq. 10 Hz. • Decimate signal with 50 to 40 Hz. • Filter signal again with cutoff freq. 0.5 Hz. • Interpolate signal • Filter out high frequency components introduced by interpolated signals contents - introduction - approach - ECG - literature - results - conclusions
For-backward filtering • Filtering: • IIR • Continuously forward • Backward over window • window > max. delay filter for all frequencies • last filtered sample is filtered value • Apply together with heart rate adaptation contents - introduction - approach - ECG - literature - results - conclusions
Which can be tried • Adaptive oscillator • FIR • IIR • For-backward filter + Heart rate adaptive filter • Envelope (but no time) contents - introduction - approach - ECG - literature - results - conclusions
Results contents - introduction - approach - ECG - literature - results - conclusions
Adaptive oscillator • The adaptive oscillator was not stable • Step-adaptation of parameters -in order to stabilize- deformed the shape of the ECG-signal • Because of fast changes of sinusoid unstable • Non-linear • Does not work when other noise is present contents - introduction - approach - ECG - literature - results - conclusions
FIR • Principle • The ideal response of an analogue filter is truncated • Length: half (180 degrees) cutoff frequency • 0.5 Hz: 1 sec; 0.05 Hz: 10 sec. • It is the standard solution • But delay >= 1 second contents - introduction - approach - ECG - literature - results - conclusions
Moving average (2000 points) contents - introduction - approach - ECG - literature - results - conclusions
Chebyshev (1000-points; 10dB sidelobe-supression) contents - introduction - approach - ECG - literature - results - conclusions
IIR • IIR • Fast (minimal one sample) • But • phase shift causes • Distortion of ECG-signal • The same delay of the signal contents - introduction - approach - ECG - literature - results - conclusions
Time-domain contents - introduction - approach - ECG - literature - results - conclusions
contents - introduction - approach - ECG - literature - results - conclusions
Frequency domain contents - introduction - approach - ECG - literature - results - conclusions
contents - introduction - approach - ECG - literature - results - conclusions
Filters Prefilter before decimation contents - introduction - approach - ECG - literature - results - conclusions
Heart rate filter contents - introduction - approach - ECG - literature - results - conclusions