biomedical signal processing lecture 2 梁 勝 富 成功大學 資訊工程系...
TRANSCRIPT
Biomedical Signal Processing
Lecture 2
梁 勝 富 成功大學 資訊工程系 [email protected]
Office: 雲平東棟 416R, Tel: Ext. 62549
Lab: 神經運算與腦機介面實驗室 ( 雲平東棟 301R)http://ncbci.csie.ncku.edu.tw/
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Outline
Typical Measurement System Analog Signal Processing
Source: Chapter 1 of Biosignal and Biomedical
Image Processing, John L. Semmlow, Marcel Dekker, ISBN: 0-8247-4803-4 3.
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Typical Measurement Systems
Typical bioengineering measurement contains Transducer: converts energy from
one form to another. Amplifier Analog Signal Processing:
Analog Filtering Analog to Digital conversion Time Sampling
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Transducers A transducer is a devices that convert
energy from one form to another. The purpose of energy conversion: to
transfer information. In measurement systems: (input)
transducers convert non-electrical energy into an electronic signal.
The exception: electrode, that converts electrical energy from ionic to electronic form.
The output: a voltage (or current), whose amplitude is proportional to the measured energy.
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Transducers The energy that is converted by the
input transducer may be generated by the physiological process itself:
cardiac pressures: pressure sensor electrical activity: E‘x’G)
indirectly related to the physiological process:
positron emission tomography (PET, 正子造影 )
an external source: e.g. x ray
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Chemical Transducer 酵素反應感測器
• 酵素轉換生物體物質 ( 例如 : 葡萄糖 ) 過程中會產生過氧化氫 (H2O2)•山葵過氧化氫酶 (horseradish peroxidase,HRP) 催化發光胺 (luminal) 與過氧化氫產生化學反應•發光胺產生氧化反應而發射光•設計 CMOS 冷光感測晶片利用光二極體吸收反應所產生的冷光並轉化成電壓訊號輸出以偵測待測物的濃度
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Chemical Transducer 酵素反應感測器
• 酵素轉換生物體物質 ( 例如 : 葡萄糖 ) 過程中會產生過氧化氫 (H2O2)•山葵過氧化氫酶 (horseradish peroxidase,HRP) 催化發光胺 (luminal) 與過氧化氫產生化學反應•發光胺產生氧化反應而發射光•設計 CMOS 冷光感測晶片利用光二極體吸收反應所產生的冷光並轉化成電壓訊號輸出以偵測待測物的濃度
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血氧感測器
•脈動含氧血紅素飽和度 (Oxy-hemoglobin saturation by pulse oximetry)
•Hb 與 HbO2 對不同光線波長之吸收率不同,分析光二極體偵測之紅光與紅外光,經換算得知血液含氧比例。
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Electrodes
Sensors from left to right:Cable harness incl. EEG, EOG and EMG electrodes, ECG electrodes,2 effort belts, snoring microphone, finger sensor, thermistor, nasal prong
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Analog Signal Processing The first stage depends on the basic
transducer operation E.g., ExG: convert the variation in
electrical property into a variation in voltage.
Single ended: constant current operation.
Different change: bridge circuit.
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Analog Signal Processing
Characteristics of Ideal Op AmpsInfinite gain for the differential input signal Zero gain for the common-mode input signal Infinite input impedances Zero output impedance Infinite bandwidth
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Noise Noise is what you do not want and
signal is what you want. Noise in biomedical measurement
Physiological variability: biological influences other than those of interest
Environmental noise or interference. E.g. fetal ECG is corrupted by the
mother’s ECG. Transducer artifact.
E.g. movement artifact Electronic noise.
thermal noise, shot noise.
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Noise White noise contains energy at all
frequencies (or at least all the frequencies of interest)
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Signal-to-Noise Ratio The relative amount of signal and noise
present in a waveform is usually quantified by the signal-to-noise ratio, SNR.
SNR is the ratio of signal to noise and both are measured in root-mean-squared (RMS) amplitude:
Matlab: 20*log10(s/n)
Matlab: 10^(db/20)
db
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Why using dB? Very small and very large magnitudes can be displayed clearly on a single plot.Linear scale 但圖上看不出大小
410)60( H
dB scale可清楚看出 dB85)60(
dBH
Notch filter: 消除某些頻率 component, 60Hz in this case.
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Analog Filters The analog filters are design to
Remove noise Condition the signal for analog-to digital
conversion (ADC) Sampling theory: a sinusoid can be
uniquely reconstructed providing it has been sampled by a least two equally spaced points over a cycle.
Any signal that contains frequency components greater than twice the sampling frequency cannot be reconstructed.
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Analog Filters Property of filters
Filter type: lowpass, high pass, band pass, etc.
Bandwidth Attenuation characteristics
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Analog Filters Filter types
Lowpass filters: allow low frequencies to pass with minimum attenuation while high frequency are attenuated.
Highpass filters: pass high frequencies but attenuate low frequencies.
Bandpass filters: reject frequencies above and below a passband region.
Bandstop filters: pass frequencies on either side of a range of attenuated frequencies.
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Bode PlotsA Bode plot shows the magnitude of a network function in decibels versus frequency using a logarithmic scale for frequency.
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Logarithmic Frequency Scales
•On a logarithmic scale, the variable is multiplied by a given factor for equalincrements of length along the axis.
•The advantage of a logarithmic frequency scale compared with linear scale is that the variations of a transfer function for a low range of frequency and the variations in a high range can be shown on a single plot.
×10 ×2
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Analog Filters Filter bandwith
The frequency range of passband: attenuation for 3 dB
E.g. Lowpass fiter: 0~cutoff frequency.
Filter order: number of energy storage element in the filter circuit. 20db/decade by adding one order
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Boundary of Passband
For Bff
707.021 BfH
2/12 BfH
Bff 稱為 half-power frequency
5.02
in
2
out2 V
VBfH
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Analog to Digital Conversion
Analog-to-digital converter (ADC) Electronic component converts an
analog voltage to an equivalent digital number.
Slicing the signal in two ways: slicing in time and slicing in amplitude.
Slicing in time: sampling (samples/sec)
Slicing in amplitude: quantization (Bits)
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Analog to Digital Conversion
•ADC allows multiple input channels to be converted.•Sampling rate for each channel = system conversion rate/# of channels
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Analog to Digital Conversion
Quantization Error Resolution: output
range/quantization level. What is the resolution of a 5-volt
and 12-bit ADC system?
Volt 0012.04096/52/5 12
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Analog to Digital Conversion
Shannon Sampling Theorem A sinusoidal waveform can be
uniquely reconstructed provided it is sampled at least twice in one period.
A continuous waveform can be reconstructed without loss of information provided the sampling frequency is greater than twice the highest frequency in the analog waveform.
max2 ff s
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Aliasing
250Hz
500Hz
750Hz
In this example, A-D conversion is 1000 Hz and the Nyquist frequency is 500 Hz. Signals of 250 and 500 Hz can be adequately portrayed in digital form. However, a frequency of 750 Hz will appear as a frequency of 250 Hz. Frequency above the Nyquist frequency are thus aliased into the recording.
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Aliasing It means if there is a 250 Hz
components in a digitized data with 1000 Hz sampling rate, the component may come from A real 250 Hz component An aliasing of a 750 Hz component
So we need analog lowpass filter to anti-aliasing before sampling.
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Aliasing%%fs=100 HzN = 100;
fs = 100;t = (1:N)/fs;
% case1:f=5Hzf5=5; n5=2*pi*f5*t;x5 = sin(n5);
figure(1)plot(t,x5)xlabel('Time (sec)');ylabel('sin(2*pi*f*t)');title('fs=100Hz, f=5Hz')
%case2:f=10 Hzf10=10; n10=2*pi*f10*t;x10 = sin(n10);
figure(2)plot(t,x10)xlabel('Time (sec)');ylabel('sin(2*pi*f*t)');title('fs=100Hz, f=10Hz')
%case3:f=75 Hzf75=75;n75=2*pi*f75*t;x75 = sin(n75);
figure(3)plot(t,x75)xlabel('Time (sec)');ylabel('sin(2*pi*f*t)');title('fs=100Hz, f=75Hz')
%case4:f=25 Hzf25=25;n25=2*pi*f25*t;x25 = sin(n25);
figure(4)plot(t,x25)xlabel('Time (sec)');ylabel('sin(2*pi*f*t)');title('fs=100Hz, f=25Hz')
%%fs600=600%case5:f=75Hz, fs=600HzN600 = 600;fs600 = 600;t600 = (1:N600)/fs600;f75=75;t600 = (1:N600)/fs600;n75_600=2*pi*f75*t600;% Generate datax75_600 = sin(n75_600);
figure(5)plot(t600,x75_600)xlabel('Time (sec)');ylabel('sin(2*pi*f*t)');title('fs=600Hz, f=75Hz')
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Analog to Digital Conversion
Nyquist frequency One half the sampling rate.
Aliasing The (highest) frequency of the
recorded signal exceeds the Nyquist frequency will cause aliasing (error).
Anti-Aliasing Increasing the sampling rate of ADC, or Filtering the analog signal before ADC.
2sf
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Data Banks Physio Net Data Bank (MTI)
http://www.physionet.org ICALAB Data Bank (Japan)
Http://www.bsp.brain.riken.go.jp/ICALAB
BCI Competition http://ida.first.fhg.de/projects/bci/
competition_iii/