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Explore the time evolution and classification of biological signals, signal acquisition systems, and digital conversion. Learn about A-D converters, frequential analysis, filtering modes, and processing of electrocardiographic signals in medical informatics.
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“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. FILTERINGPERIODICAL SIGNALS PROCESSING COURSE 7
1.1. DEFINITION • TIME EVOLUTION OF A BIOLOGICAL VARIABLE • GENERAL SCHEME OF BIOSIGNAL ANALYSIS
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)
1.3. AQUISITION SYSTEMS • ELECTRICAL SIGNALS : electrodes • NON-ELECTRICAL: transducers • (pH, pressure etc)
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)
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)
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)
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)
1.4. FREQUENTIAL ANALYSIS • SIGNAL REPRESENTATION: • TEMPORAL Ampl = f (time) • FREQUENTIAL (spectrum) Ampl = f (freq)
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)
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
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)
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)
3. PROCESSING PERIODICAL SIGNALSELECTROCARDIOGRAPHIC SIGNAL (ECG)
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
3.3. ECG ANALYSIS: • RYTHM • INTERVALS • AMPLITUDES • SLOPES • 3.4. OTHER ANALYSES: • VECTOCARDIOGRAMS • CARDIAC MAPPING • LATE POTENTIALS, ARRHYTMIAS