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“Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA

“Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA. DEPARTMENT OF MEDICAL INFORMATICS AND BIOPHYSICS Medical Informatics Division www.medinfo.umft.ro/dim 2007 / 2008. BIOLOGICAL SIGNALS (I) AQUISITION. FILTERING PERIODICAL SIGNALS PROCESSING. COURSE 7.

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“Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA

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  1. “Victor Babes” UNIVERSITY OF MEDICINE AND PHARMACY TIMISOARA DEPARTMENT OF MEDICAL INFORMATICS AND BIOPHYSICS Medical Informatics Division www.medinfo.umft.ro/dim 2007 / 2008

  2. BIOLOGICAL SIGNALS (I)AQUISITION. FILTERINGPERIODICAL SIGNALS PROCESSING COURSE 7

  3. 1. BIOLOGICAL SIGNALS AQUISITION

  4. 1.1. DEFINITION • TIME EVOLUTION OF A BIOLOGICAL VARIABLE • GENERAL SCHEME OF BIOSIGNAL ANALYSIS

  5. 1.2. CLASSIFICATION • a) ON THEIR NATURE: • ELECTRICAL (ECG, EEG, EMG etc) • NON-ELECTRICAL (pressure, concentration etc) • b) ON EVOLUTION • PERIODICAL (ECG) • NON-PERIODICAL (EEG)

  6. 1.3. AQUISITION SYSTEMS • ELECTRICAL SIGNALS : electrodes • NON-ELECTRICAL: transducers • (pH, pressure etc)

  7. 1.4. ANALOG - DIGITAL CONVERSION • a) SAMPLING • DISCRETIZATION ON OX AXIS (time) • SAMPLING PERIOD: Te (s) • Time interval between two successive readings • SAMPLING FREQUENCY: fe (Hz) • Number of readings in time unit (nr./sec) fe = 1 / Te (1)

  8. Example: recorded signal

  9. SAMPLING

  10. SAMPLING

  11. SAMPLING

  12. SAMPLING

  13. a) SAMPLING THEOREM (Shannon) fe >= 2 . Fmax (2) • Sampling frequency should be at least twice the maximal frequency of the signal • NYQUIST FREQUENCY: 2.Fmax (Hz)

  14. Good sampling

  15. b) QUANTISING • Discretization of OY axis (amplitude) • INTERVAL BETWEEN VMAX AND VMIN IS DIVIDED INTO “N” AMPLITUDE STEPS • THE WIDTH OF A STEP (Quantum) D V = (V Max - V min ) / N(3) • Relation of N with n – number of bits used by ADC to express a reading N = 2 n (4)

  16. Quantising

  17. 1.5. A - D CONVERTERS • MAXIMAL SAMPLING FREQUENCY (10 kHz - 1 MHz) • NUMBER OF BITS (8 - 16) • INPUT RANGE (-10/+10 V, -0.1/+0.1 v) • NUMBER OF CHANNELS (MULTIPLEXING)

  18. 1.4. FREQUENTIAL ANALYSIS • SIGNAL REPRESENTATION: • TEMPORAL Ampl = f (time) • FREQUENTIAL (spectrum) Ampl = f (freq)

  19. b) FILTER ANALYSIS • BAND - PASS FILTERS ( d, q, a, b ) • WAVES PROPORTIONS - mingographs • c) FOURIER ANALYSIS • Definition: SIGNAL DECOMPOSITION INTO FREQUENCIAL COMPONENTS • Domain: 0 - 30 Hz • Types of spectra: • AMPLITUDE • POWER (proportional to A2)

  20. Exemplu: semnal sinusoidal de 1 Hertz si spectrul sau

  21. Semnal de 2 Hz

  22. c) SPECTRAL RESOLUTION • DEFINITION: distance between two neighbour points in the spectrum • RELATION WITH EPOCH LENGTH (recorded signal duration, in seconds) D f = 1 / D T (5) • d) TIME CONSTANT • e) TESTS FOR SIGNALS • STATIONARITY, NORMALITY AND TREND TESTS

  23. Exemple - problem • We record an EMG signal using a 10 bit ADC, with a sampling frequency of 500 Hz, recording epochs of 2 seconds. The input signal has values between 0 and 100 mV. Calculate: • Sampling period (in ms) • Maximal frequency in the spectrum • Spectral resolution • Number of amplitude steps • Reading precision (quantum value, how many mV correspond to 1 bit)

  24. 2. FILTERING

  25. 2.1. DEFINITION: removing or diminishing the perturbations 2.2. NOISE CLASSIFICATION (perturbations): a) PERIODICAL (pink noise = low frequencies) b) NON-PERIODICAL (white noise) 2.3. SIGNAL / NOISE RATIO (SNR, decibels dB) 2.4. FILTERING MODES ELECTRONIC FILTER (before ADC) NUMERIC FILTER (after ADC)

  26. 2.5. TYPES OF FILTERS

  27. 3. PROCESSING PERIODICAL SIGNALSELECTROCARDIOGRAPHIC SIGNAL (ECG)

  28. 3.2. ECG PROCESSING - PHASES

  29. b) ARTIFACT ELIMINATION • ZERO LINE • SMOOTHING • c) QRS TYPIFICATION • d) ST - T TYPIFICATION • ST SEGMENT AMPLITUDE • (in coronary diseases) • e) P - WAVE DETECTION • VERY SMALL AMPLITUDE

  30. 3.3. ECG ANALYSIS: • RYTHM • INTERVALS • AMPLITUDES • SLOPES • 3.4. OTHER ANALYSES: • VECTOCARDIOGRAMS • CARDIAC MAPPING • LATE POTENTIALS, ARRHYTMIAS

  31. - e n d -

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