Behandling af biologiske signaler 2
Behandling af biologiske signaler 2
Behandling af biologiske signaler 2
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Måling, behandling og<br />
præsentation <strong>af</strong><br />
<strong>biologiske</strong> <strong>signaler</strong><br />
mm5<br />
Pascal Madeleine<br />
Matrixlaboratory<br />
Indhold<br />
Introduktion til matricer og numeriske beregninger<br />
Gr<strong>af</strong>ik i 2- og 3-D<br />
Programmering i MATLAB, m-filer<br />
Signal behandling 1<br />
Signal behandling 2<br />
Basic<br />
instrumentation<br />
system<br />
Mål<br />
Måling, behandling<br />
og præsentation <strong>af</strong><br />
<strong>biologiske</strong> <strong>signaler</strong><br />
At give en introduktion til måling, behandling og<br />
præsentation <strong>af</strong> <strong>biologiske</strong> <strong>signaler</strong>.<br />
Matrixlaboratory<br />
Indhold<br />
Introduktion til matricer og numeriske beregninger<br />
Gr<strong>af</strong>ik i 2- og 3-D<br />
Programmering i MATLAB, m-filer<br />
Signal behandling 1<br />
Signal behandling 2<br />
files load data mean average plot<br />
graph<br />
filename variables<br />
Data flow<br />
variables<br />
save<br />
save<br />
filename 2
Vernier Logger/Mr Kick<br />
cmbl/txt files<br />
– See mm 4<br />
Mat files from Mr kick<br />
– All purposes recording system developed by<br />
knl (knl@hst.aau.dk) at SMI<br />
Matlab code<br />
Advanced version<br />
(generic version)<br />
Vernier Logger/Mr Kick<br />
cmbl/txt files<br />
– See mm 4<br />
Mat files from Mr kick<br />
– All purposes recording system developed by<br />
knl (knl@hst.aau.dk) at SMI<br />
Variables
files load data mean average plot<br />
graph<br />
filename variables<br />
Data flow<br />
variables<br />
Filters and frequency response<br />
save<br />
save<br />
filename 2<br />
Filters are used to modify the frequency contents<br />
of input signals<br />
Low-pass (LP) filters attenuate the frequency<br />
contents of a signal above a certain cut-off<br />
frequency f c<br />
High-pass (HP) filters attenuate the frequency<br />
contents below a certain cut-off frequency f c<br />
Filters and frequency response<br />
High-pass Low-pass<br />
Band-pass Band-stop<br />
Bioelectric signal properties Amplification<br />
of the signal, reduction of noise and prevention of<br />
aliasing<br />
Filters and frequency response<br />
Filters are used to modify the frequency contents<br />
of input signals<br />
Band-pass filters are formed by cascading a LP<br />
and a HP filter and vice versa for a band-stop filter<br />
Digital filter in Matlab<br />
Types: Bessels, Butterworth, Chebyshev,…<br />
How to define a band-pass filter<br />
[b,a] = butter(2,Fc1/(Fs/2)); %Butterworth<br />
low pass filter order 2, Fcut =Fc1<br />
[d,c] = butter(2,Fc2/(Fs/2),'high');<br />
%Butterworth high pass filter order 2, Fcut<br />
=Fc2
Digital filter in Matlab<br />
%EMG Filtering<br />
for i=1:length(dath001)<br />
EMG<strong>af</strong>(:,i) = filtfilt(b,a,dath0001(:,1)); %LP filter<br />
end<br />
for i=1:size(dath001)<br />
EMG<strong>af</strong>(:,i) = filtfilt(d,c, dath0001(:,i)); %HP filter<br />
end<br />
Digital filter in Matlab<br />
Biosignal processing<br />
Representation of biosignals<br />
The time domain is used to represent changes in<br />
signal amplitude with time<br />
Features can then be extracted:<br />
a latency (EP),<br />
an amplitude<br />
(peak-peak value, RMS, ARV),<br />
…<br />
Digital filter in Matlab<br />
files load data mean average plot<br />
graph<br />
filename variables<br />
Data flow<br />
Ramp contraction<br />
Isometric elbow flexion<br />
(N=12)<br />
Static: 0-10-30-50-70%<br />
Ramp: 0-50% MVC (2%/s)<br />
Injection of a bolus of<br />
hypertonic saline to elicit<br />
acute experimental<br />
muscle pain<br />
Isotonic saline as control<br />
variables<br />
save<br />
save<br />
filename 2
Amplitude processing methods<br />
Estimator Continuous<br />
time<br />
ARV<br />
or<br />
MAV<br />
RMS<br />
ARV<br />
RMS<br />
Amplitude<br />
Processing<br />
methods<br />
ARV or<br />
mean values<br />
During<br />
acute<br />
muscle pain<br />
Increased<br />
MMG (P
Fourier<br />
Transform<br />
(FT)<br />
% Example for one ECG signal<br />
tfekg=fft(ekg,512); % Fourier Transform of the signal<br />
f=(0:255)/256*(100/2) % Scale frequency vector (Fs was 100 Hz)<br />
plot(f,abs(tfekg(1:256)’))<br />
Matrixlaboratory<br />
Indhold<br />
Introduktion til matricer og numeriske beregninger<br />
Gr<strong>af</strong>ik i 2- og 3-D<br />
Programmering i MATLAB, m-filer<br />
Signal behandling 1<br />
Signal behandling 2<br />
Fourier<br />
Transform<br />
(FT)<br />
% Example for one EMG signal with 50 Hz interference<br />
tfemg=fft(emg,1024); % Fourier Transform of the signal<br />
f=(0:512)/512*(1000/2) % Scale frequency vector (Fs: 1000 Hz)<br />
plot(f,abs(tfemg(1:512)’))
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