diff --git a/docs/compte-rendu.md b/docs/compte-rendu.md
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+---
+title: "Compte rendu TP carrefour"
+author: John Doe
+geometry: margin=1cm
+output: pdf_document
+mainfont: sans-serif
+---
+
+
+
+
+
+# Compte rendu du TP Carrefour
+
+## Diagramme de la FSM
+
+
+
+
+## Questions
+
+### Question 1 : Combien de LUT sont utilisées ?
+
+### Question 2 : Combien de Flip Flop sont utilisées, est-ce cohérent avec le VHDL ?
+
+### Question 3 : Combien de latchs sont utilisées ? Pourquoi ?
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diff --git a/src-ref/octaveScript.m b/src-ref/octaveScript.m
new file mode 100644
index 0000000000000000000000000000000000000000..d62a75414a64973aa406e1ea96425b8160aa4a18
--- /dev/null
+++ b/src-ref/octaveScript.m
@@ -0,0 +1,57 @@
+% ECG telecharge de
+%https://archive.physionet.org/cgi-bin/atm/ATM
+%Echantillonne à 500Hz (F_Nyquist = 250Hz)
+% Script OCTAVE (pas matlab...)
+
+Fs = 500; % Frequence d'echantillonnage
+Fn = Fs/2; % Frequence de Nyquist
+figure(1)
+T = csvread('./ADCSamplesOctave.csv');
+subplot(2,3,1);plot(T(:,2));title('Raw ECG signal');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (output of an 11-bit ADC)');
+
+% Pourc Octave (a supprimer sous Matlab)
+pkg load signal;
+
+%Pour les trois filtres suivants, on peut jouer sur les ordres
+% donc le nombre de coefficients des filtres numeriques
+
+%suppression de la baseline
+fBaseLine=fir1(128, 5/Fn, 'high');
+y_minus_BL=filter(fBaseLine,[1],T(:,2));
+subplot(2,3,2);plot(y_minus_BL);title('Baseline wander reduced');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (digital signal)');
+subplot(2,3,3);plot(y_minus_BL(1:1000));title('Baseline wander reduced -- zoomed');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (digital signal)');
+
+
+%elimination du bruit à 50Hz par un coupe-bande tout basique
+f50Hz=fir1(100, [45 55]/Fn, 'stop');
+y_minus_50Hz_simple = filter(f50Hz,[1],y_minus_BL);
+subplot(2,3,4);plot(y_minus_50Hz_simple(1:1000));title('FIR1 band-cut-- zoomed');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (digital signal)');
+
+%elimination du bruit à 50Hz par un coupe-bande plus elabore
+[b,a]=pei_tseng_notch ( 50 / Fn, 10/Fn );
+y_minus_50Hz_pei_tseng = filter(b,a,y_minus_BL);
+subplot(2,3,5);plot(y_minus_50Hz_pei_tseng(1:1000));title('Pei Tseng band-cut -- zoomed');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (digital signal)');
+
+%lissage du bruit haute frequence par filtre de Parks-McClellan
+Fpass = 50;
+Fstop = 60;
+F = [0 Fpass Fstop Fn]/(Fn);
+A = [1 1 0 0];
+fLP = remez(10,F,A); % Voir pour Matlab: firpm
+yLP = filter(fLP,[1],y_minus_50Hz_pei_tseng);
+
+subplot(2,3,6);plot(yLP(1:1000));title('Low-pass filter to suppress high-freq noise -- zoomed');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (digital signal)');
+figure(2)
+subplot(2,1,1);plot(T(:,2));title('Raw ECG signal');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (digital signal)');
+subplot(2,1,2);plot(yLP);title('After 3 filters');xlabel('Samples (Fs=500Hz)');ylabel('Magnitude (digital signal)');
+print(2, "ECG_raw_3filters.pdf", "-dpdflatexstandalone");
+figure(3)
+
+%L'artillerie lourde: fonction intégrant la methode de Pan-Tompkin
+%merci Sedghamiz. H !!!
+pan_tompkin(T(:,2),500,1)
+
+
+
+
+
diff --git a/src-ref/pan_tompkin.m b/src-ref/pan_tompkin.m
new file mode 100644
index 0000000000000000000000000000000000000000..b235740c9d01c6022550e012e77fb61784e47159
--- /dev/null
+++ b/src-ref/pan_tompkin.m
@@ -0,0 +1,369 @@
+function [qrs_amp_raw,qrs_i_raw,delay]=pan_tompkin(ecg,fs,gr)
+%% function [qrs_amp_raw,qrs_i_raw,delay]=pan_tompkin(ecg,fs)
+% Complete implementation of Pan-Tompkins algorithm
+%% Inputs
+% ecg : raw ecg vector signal 1d signal
+% fs : sampling frequency e.g. 200Hz, 400Hz and etc
+% gr : flag to plot or not plot (set it 1 to have a plot or set it zero not
+% to see any plots
+%% Outputs
+% qrs_amp_raw : amplitude of R waves amplitudes
+% qrs_i_raw : index of R waves
+% delay : number of samples which the signal is delayed due to the
+% filtering
+%% Method
+% See Ref and supporting documents on researchgate.
+% https://www.researchgate.net/publication/313673153_Matlab_Implementation_of_Pan_Tompkins_ECG_QRS_detector
+%% References :
+%[1] Sedghamiz. H, "Matlab Implementation of Pan Tompkins ECG QRS
+%detector.",2014. (See researchgate)
+%[2] PAN.J, TOMPKINS. W.J,"A Real-Time QRS Detection Algorithm" IEEE
+%TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. BME-32, NO. 3, MARCH 1985.
+%% ============== Licensce ========================================== %%
+% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+% "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+% FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+% OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+% SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
+% TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+% PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+% LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+% NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+% Author :
+% Hooman Sedghamiz, Feb, 2018
+% MSc. Biomedical Engineering, Linkoping University
+% Email : Hooman.sedghamiz@gmail.com
+%% ============ Update History ================== %%
+% Feb 2018 :
+% 1- Cleaned up the code and added more comments
+% 2- Added to BioSigKit Toolbox
+%% ================= Now Part of BioSigKit ==================== %%
+if ~isvector(ecg)
+ error('ecg must be a row or column vector');
+end
+if nargin < 3
+ gr = 1; % on default the function always plots
+end
+ecg = ecg(:); % vectorize
+%% ======================= Initialize =============================== %
+delay = 0;
+skip = 0; % becomes one when a T wave is detected
+m_selected_RR = 0;
+mean_RR = 0;
+ser_back = 0;
+ax = zeros(1,6);
+%% ============ Noise cancelation(Filtering)( 5-15 Hz) =============== %%
+if fs == 200
+% ------------------ remove the mean of Signal -----------------------%
+ ecg = ecg - mean(ecg);
+%% ==== Low Pass Filter H(z) = ((1 - z^(-6))^2)/(1 - z^(-1))^2 ==== %%
+%%It has come to my attention the original filter doesnt achieve 12 Hz
+% b = [1 0 0 0 0 0 -2 0 0 0 0 0 1];
+% a = [1 -2 1];
+% ecg_l = filter(b,a,ecg);
+% delay = 6;
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ Wn = 12*2/fs;
+ N = 3; % order of 3 less processing
+ [a,b] = butter(N,Wn,'low'); % bandpass filtering
+ ecg_l = filtfilt(a,b,ecg);
+ ecg_l = ecg_l/ max(abs(ecg_l));
+ %% ======================= start figure ============================= %%
+ if gr
+ figure;
+ ax(1) = subplot(321);plot(ecg);axis tight;title('Raw signal');
+ ax(2)=subplot(322);plot(ecg_l);axis tight;title('Low pass filtered');
+ end
+%% ==== High Pass filter H(z) = (-1+32z^(-16)+z^(-32))/(1+z^(-1)) ==== %%
+%%It has come to my attention the original filter doesn achieve 5 Hz
+% b = zeros(1,33);
+% b(1) = -1; b(17) = 32; b(33) = 1;
+% a = [1 1];
+% ecg_h = filter(b,a,ecg_l); % Without Delay
+% delay = delay + 16;
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ Wn = 5*2/fs;
+ N = 3; % order of 3 less processing
+ [a,b] = butter(N,Wn,'high'); % bandpass filtering
+ ecg_h = filtfilt(a,b,ecg_l);
+ ecg_h = ecg_h/ max(abs(ecg_h));
+ if gr
+ ax(3)=subplot(323);plot(ecg_h);axis tight;title('High Pass Filtered');
+ end
+else
+%% bandpass filter for Noise cancelation of other sampling frequencies(Filtering)
+ f1=5; % cuttoff low frequency to get rid of baseline wander
+ f2=15; % cuttoff frequency to discard high frequency noise
+ Wn=[f1 f2]*2/fs; % cutt off based on fs
+ N = 3; % order of 3 less processing
+ [a,b] = butter(N,Wn); % bandpass filtering
+ ecg_h = filtfilt(a,b,ecg);
+ ecg_h = ecg_h/ max( abs(ecg_h));
+ if gr
+ ax(1) = subplot(3,2,[1 2]);plot(ecg);axis tight;title('Raw Signal');
+ ax(3)=subplot(323);plot(ecg_h);axis tight;title('Band Pass Filtered');
+ end
+end
+%% ==================== derivative filter ========================== %%
+% ------ H(z) = (1/8T)(-z^(-2) - 2z^(-1) + 2z + z^(2)) --------- %
+if fs ~= 200
+ int_c = (5-1)/(fs*1/40);
+ b = interp1(1:5,[1 2 0 -2 -1].*(1/8)*fs,1:int_c:5);
+else
+ b = [1 2 0 -2 -1].*(1/8)*fs;
+end
+ ecg_d = filtfilt(b,1,ecg_h);
+ ecg_d = ecg_d/max(ecg_d);
+ if gr
+ ax(4)=subplot(324);plot(ecg_d);
+ axis tight;
+ title('Filtered with the derivative filter');
+ end
+%% ========== Squaring nonlinearly enhance the dominant peaks ========== %%
+ ecg_s = ecg_d.^2;
+ if gr
+ ax(5)=subplot(325);
+ plot(ecg_s);
+ axis tight;
+ title('Squared');
+ end
+%% ============ Moving average ================== %%
+%-------Y(nt) = (1/N)[x(nT-(N - 1)T)+ x(nT - (N - 2)T)+...+x(nT)]---------%
+ecg_m = conv(ecg_s ,ones(1 ,round(0.150*fs))/round(0.150*fs));
+delay = delay + round(0.150*fs)/2;
+ if gr
+ ax(6)=subplot(326);plot(ecg_m);
+ axis tight;
+ title('Averaged with 30 samples length,Black noise,Green Adaptive Threshold,RED Sig Level,Red circles QRS adaptive threshold');
+ axis tight;
+ end
+%% ===================== Fiducial Marks ============================== %%
+% Note : a minimum distance of 40 samples is considered between each R wave
+% since in physiological point of view no RR wave can occur in less than
+% 200 msec distance
+[pks,locs] = findpeaks(ecg_m,'MINPEAKDISTANCE',round(0.2*fs));
+%% =================== Initialize Some Other Parameters =============== %%
+LLp = length(pks);
+% ---------------- Stores QRS wrt Sig and Filtered Sig ------------------%
+qrs_c = zeros(1,LLp); % amplitude of R
+qrs_i = zeros(1,LLp); % index
+qrs_i_raw = zeros(1,LLp); % amplitude of R
+qrs_amp_raw= zeros(1,LLp); % Index
+% ------------------- Noise Buffers ---------------------------------%
+nois_c = zeros(1,LLp);
+nois_i = zeros(1,LLp);
+% ------------------- Buffers for Signal and Noise ----------------- %
+SIGL_buf = zeros(1,LLp);
+NOISL_buf = zeros(1,LLp);
+SIGL_buf1 = zeros(1,LLp);
+NOISL_buf1 = zeros(1,LLp);
+THRS_buf1 = zeros(1,LLp);
+THRS_buf = zeros(1,LLp);
+%% initialize the training phase (2 seconds of the signal) to determine the THR_SIG and THR_NOISE
+THR_SIG = max(ecg_m(1:2*fs))*1/3; % 0.25 of the max amplitude
+THR_NOISE = mean(ecg_m(1:2*fs))*1/2; % 0.5 of the mean signal is considered to be noise
+SIG_LEV= THR_SIG;
+NOISE_LEV = THR_NOISE;
+%% Initialize bandpath filter threshold(2 seconds of the bandpass signal)
+THR_SIG1 = max(ecg_h(1:2*fs))*1/3; % 0.25 of the max amplitude
+THR_NOISE1 = mean(ecg_h(1:2*fs))*1/2;
+SIG_LEV1 = THR_SIG1; % Signal level in Bandpassed filter
+NOISE_LEV1 = THR_NOISE1; % Noise level in Bandpassed filter
+%% ============ Thresholding and desicion rule ============= %%
+Beat_C = 0; % Raw Beats
+Beat_C1 = 0; % Filtered Beats
+Noise_Count = 0; % Noise Counter
+for i = 1 : LLp
+ %% ===== locate the corresponding peak in the filtered signal === %%
+ if locs(i)-round(0.150*fs)>= 1 && locs(i)<= length(ecg_h)
+ [y_i,x_i] = max(ecg_h(locs(i)-round(0.150*fs):locs(i)));
+ else
+ if i == 1
+ [y_i,x_i] = max(ecg_h(1:locs(i)));
+ ser_back = 1;
+ elseif locs(i)>= length(ecg_h)
+ [y_i,x_i] = max(ecg_h(locs(i)-round(0.150*fs):end));
+ end
+ end
+ %% ================= update the heart_rate ==================== %%
+ if Beat_C >= 9
+ diffRR = diff(qrs_i(Beat_C-8:Beat_C)); % calculate RR interval
+ mean_RR = mean(diffRR); % calculate the mean of 8 previous R waves interval
+ comp =qrs_i(Beat_C)-qrs_i(Beat_C-1); % latest RR
+
+ if comp <= 0.92*mean_RR || comp >= 1.16*mean_RR
+ % ------ lower down thresholds to detect better in MVI -------- %
+ THR_SIG = 0.5*(THR_SIG);
+ THR_SIG1 = 0.5*(THR_SIG1);
+ else
+ m_selected_RR = mean_RR; % The latest regular beats mean
+ end
+
+ end
+
+ %% == calculate the mean last 8 R waves to ensure that QRS is not ==== %%
+ if m_selected_RR
+ test_m = m_selected_RR; %if the regular RR availabe use it
+ elseif mean_RR && m_selected_RR == 0
+ test_m = mean_RR;
+ else
+ test_m = 0;
+ end
+
+ if test_m
+ if (locs(i) - qrs_i(Beat_C)) >= round(1.66*test_m) % it shows a QRS is missed
+ [pks_temp,locs_temp] = max(ecg_m(qrs_i(Beat_C)+ round(0.200*fs):locs(i)-round(0.200*fs))); % search back and locate the max in this interval
+ locs_temp = qrs_i(Beat_C)+ round(0.200*fs) + locs_temp -1; % location
+
+ if pks_temp > THR_NOISE
+ Beat_C = Beat_C + 1;
+ qrs_c(Beat_C) = pks_temp;
+ qrs_i(Beat_C) = locs_temp;
+ % ------------- Locate in Filtered Sig ------------- %
+ if locs_temp <= length(ecg_h)
+ [y_i_t,x_i_t] = max(ecg_h(locs_temp-round(0.150*fs):locs_temp));
+ else
+ [y_i_t,x_i_t] = max(ecg_h(locs_temp-round(0.150*fs):end));
+ end
+ % ----------- Band pass Sig Threshold ------------------%
+ if y_i_t > THR_NOISE1
+ Beat_C1 = Beat_C1 + 1;
+ qrs_i_raw(Beat_C1) = locs_temp-round(0.150*fs)+ (x_i_t - 1);% save index of bandpass
+ qrs_amp_raw(Beat_C1) = y_i_t; % save amplitude of bandpass
+ SIG_LEV1 = 0.25*y_i_t + 0.75*SIG_LEV1; % when found with the second thres
+ end
+
+ not_nois = 1;
+ SIG_LEV = 0.25*pks_temp + 0.75*SIG_LEV ; % when found with the second threshold
+ end
+ else
+ not_nois = 0;
+ end
+ end
+
+ %% =================== find noise and QRS peaks ================== %%
+ if pks(i) >= THR_SIG
+ % ------ if No QRS in 360ms of the previous QRS See if T wave ------%
+ if Beat_C >= 3
+ if (locs(i)-qrs_i(Beat_C)) <= round(0.3600*fs)
+ Slope1 = mean(diff(ecg_m(locs(i)-round(0.075*fs):locs(i)))); % mean slope of the waveform at that position
+ Slope2 = mean(diff(ecg_m(qrs_i(Beat_C)-round(0.075*fs):qrs_i(Beat_C)))); % mean slope of previous R wave
+ if abs(Slope1) <= abs(0.5*(Slope2)) % slope less then 0.5 of previous R
+ Noise_Count = Noise_Count + 1;
+ nois_c(Noise_Count) = pks(i);
+ nois_i(Noise_Count) = locs(i);
+ skip = 1; % T wave identification
+ % ----- adjust noise levels ------ %
+ NOISE_LEV1 = 0.125*y_i + 0.875*NOISE_LEV1;
+ NOISE_LEV = 0.125*pks(i) + 0.875*NOISE_LEV;
+ else
+ skip = 0;
+ end
+
+ end
+ end
+ %---------- skip is 1 when a T wave is detected -------------- %
+ if skip == 0
+ Beat_C = Beat_C + 1;
+ qrs_c(Beat_C) = pks(i);
+ qrs_i(Beat_C) = locs(i);
+
+ %--------------- bandpass filter check threshold --------------- %
+ if y_i >= THR_SIG1
+ Beat_C1 = Beat_C1 + 1;
+ if ser_back
+ qrs_i_raw(Beat_C1) = x_i; % save index of bandpass
+ else
+ qrs_i_raw(Beat_C1)= locs(i)-round(0.150*fs)+ (x_i - 1); % save index of bandpass
+ end
+ qrs_amp_raw(Beat_C1) = y_i; % save amplitude of bandpass
+ SIG_LEV1 = 0.125*y_i + 0.875*SIG_LEV1; % adjust threshold for bandpass filtered sig
+ end
+ SIG_LEV = 0.125*pks(i) + 0.875*SIG_LEV ; % adjust Signal level
+ end
+
+ elseif (THR_NOISE <= pks(i)) && (pks(i) < THR_SIG)
+ NOISE_LEV1 = 0.125*y_i + 0.875*NOISE_LEV1; % adjust Noise level in filtered sig
+ NOISE_LEV = 0.125*pks(i) + 0.875*NOISE_LEV; % adjust Noise level in MVI
+ elseif pks(i) < THR_NOISE
+ Noise_Count = Noise_Count + 1;
+ nois_c(Noise_Count) = pks(i);
+ nois_i(Noise_Count) = locs(i);
+ NOISE_LEV1 = 0.125*y_i + 0.875*NOISE_LEV1; % noise level in filtered signal
+ NOISE_LEV = 0.125*pks(i) + 0.875*NOISE_LEV; % adjust Noise level in MVI
+ end
+
+ %% ================== adjust the threshold with SNR ============= %%
+ if NOISE_LEV ~= 0 || SIG_LEV ~= 0
+ THR_SIG = NOISE_LEV + 0.25*(abs(SIG_LEV - NOISE_LEV));
+ THR_NOISE = 0.5*(THR_SIG);
+ end
+
+ %------ adjust the threshold with SNR for bandpassed signal -------- %
+ if NOISE_LEV1 ~= 0 || SIG_LEV1 ~= 0
+ THR_SIG1 = NOISE_LEV1 + 0.25*(abs(SIG_LEV1 - NOISE_LEV1));
+ THR_NOISE1 = 0.5*(THR_SIG1);
+ end
+
+
+%--------- take a track of thresholds of smoothed signal -------------%
+SIGL_buf(i) = SIG_LEV;
+NOISL_buf(i) = NOISE_LEV;
+THRS_buf(i) = THR_SIG;
+%-------- take a track of thresholds of filtered signal ----------- %
+SIGL_buf1(i) = SIG_LEV1;
+NOISL_buf1(i) = NOISE_LEV1;
+THRS_buf1(i) = THR_SIG1;
+% ----------------------- reset parameters -------------------------- %
+skip = 0;
+not_nois = 0;
+ser_back = 0;
+end
+%% ======================= Adjust Lengths ============================ %%
+qrs_i_raw = qrs_i_raw(1:Beat_C1);
+qrs_amp_raw = qrs_amp_raw(1:Beat_C1);
+qrs_c = qrs_c(1:Beat_C);
+qrs_i = qrs_i(1:Beat_C);
+%% ======================= Plottings ================================= %%
+if gr
+ hold on,scatter(qrs_i,qrs_c,'m');
+ hold on,plot(locs,NOISL_buf,'--k','LineWidth',2);
+ hold on,plot(locs,SIGL_buf,'--r','LineWidth',2);
+ hold on,plot(locs,THRS_buf,'--g','LineWidth',2);
+ if any(ax)
+ ax(~ax) = [];
+ linkaxes(ax,'x');
+ zoom on;
+ end
+end
+%% ================== overlay on the signals ========================= %%
+ if gr
+ figure;
+ az(1)=subplot(311);
+ plot(ecg_h);
+ title('QRS on Filtered Signal');
+ axis tight;
+ hold on,scatter(qrs_i_raw,qrs_amp_raw,'m');
+ hold on,plot(locs,NOISL_buf1,'LineWidth',2,'Linestyle','--','color','k');
+ hold on,plot(locs,SIGL_buf1,'LineWidth',2,'Linestyle','-.','color','r');
+ hold on,plot(locs,THRS_buf1,'LineWidth',2,'Linestyle','-.','color','g');
+ az(2)=subplot(312);plot(ecg_m);
+ title('QRS on MVI signal and Noise level(black),Signal Level (red) and Adaptive Threshold(green)');axis tight;
+ hold on,scatter(qrs_i,qrs_c,'m');
+ hold on,plot(locs,NOISL_buf,'LineWidth',2,'Linestyle','--','color','k');
+ hold on,plot(locs,SIGL_buf,'LineWidth',2,'Linestyle','-.','color','r');
+ hold on,plot(locs,THRS_buf,'LineWidth',2,'Linestyle','-.','color','g');
+ az(3)=subplot(313);
+ plot(ecg-mean(ecg));
+ title('Pulse train of the found QRS on ECG signal');
+ axis tight;
+ line(repmat(qrs_i_raw,[2 1]),...
+ repmat([min(ecg-mean(ecg))/2; max(ecg-mean(ecg))/2],size(qrs_i_raw)),...
+ 'LineWidth',2.5,'LineStyle','-.','Color','r');
+ linkaxes(az,'x');
+ zoom on;
+ end
+end
+