[R] Conversion of Matlab code to an R code

Bert Gunter gunter.berton at gene.com
Mon Mar 23 16:23:48 CET 2015


1. Yes. Both are Turing complete .

2. Someone here may be willing to help you if you're lucky, but the
standard recommendation is: Do your homework and learn R!  (There are
many good tutorials and resources available).

3. In future, post in plain text, not HTML, as the posting guide asks.

Cheers,
Bert

Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374

"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll




On Mon, Mar 23, 2015 at 8:10 AM, Abhinaba Roy <abhinabaroy09 at gmail.com> wrote:
> Hi,
>
> Can a Matlab code be converted to R code?
>
> I am finding it difficult to do so.
>
> Could you please help me out with it.
>
> Your help will be highly appreciated.
>
> Here comes the Matlab code
> ##############
> 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
> qrs_c =[]; %amplitude of R
> qrs_i =[]; %index
> SIG_LEV = 0;
> nois_c =[];
> nois_i =[];
> delay = 0;
> skip = 0; % becomes one when a T wave is detected
> not_nois = 0; % it is not noise when not_nois = 1
> selected_RR =[]; % Selected RR intervals
> m_selected_RR = 0;
> mean_RR = 0;
> qrs_i_raw =[];
> qrs_amp_raw=[];
> ser_back = 0;
> test_m = 0;
> SIGL_buf = [];
> NOISL_buf = [];
> THRS_buf = [];
> SIGL_buf1 = [];
> NOISL_buf1 = [];
> THRS_buf1 = [];
>
>
> %% Plot differently based on filtering settings
> if gr
>  if fs == 200
>   figure,  ax(1)=subplot(321);plot(ecg);axis tight;title('Raw ECG Signal');
>  else
>   figure,  ax(1)=subplot(3,2,[1 2]);plot(ecg);axis tight;title('Raw ECG
> Signal');
>  end
> end
> %% Noise cancelation(Filtering) % Filters (Filter in between 5-15 Hz)
> if fs == 200
> %% Low Pass Filter  H(z) = ((1 - z^(-6))^2)/(1 - z^(-1))^2
> b = [1 0 0 0 0 0 -2 0 0 0 0 0 1];
> a = [1 -2 1];
> h_l = filter(b,a,[1 zeros(1,12)]);
> ecg_l = conv (ecg ,h_l);
> ecg_l = ecg_l/ max( abs(ecg_l));
> delay = 6; %based on the paper
> if gr
> 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))
> b = [-1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 -32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1];
> a = [1 -1];
> h_h = filter(b,a,[1 zeros(1,32)]);
> ecg_h = conv (ecg_l ,h_h);
> ecg_h = ecg_h/ max( abs(ecg_h));
> delay = delay + 16; % 16 samples for highpass filtering
> 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(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))
> h_d = [-1 -2 0 2 1]*(1/8);%1/8*fs
> ecg_d = conv (ecg_h ,h_d);
> ecg_d = ecg_d/max(ecg_d);
> delay = delay + 2; % delay of derivative filter 2 samples
> 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 + 15;
>
> 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 Mark
> % 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 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 online desicion rule
>
> for i = 1 : length(pks)
>
>    %% 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 (Two heart rate means one the moste recent and
> the other selected)
>     if length(qrs_c) >= 9
>
>         diffRR = diff(qrs_i(end-8:end)); %calculate RR interval
>         mean_RR = mean(diffRR); % calculate the mean of 8 previous R waves
> interval
>         comp =qrs_i(end)-qrs_i(end-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_NOISE = 0.5*(THR_SIG);
>                % lower down thresholds to detect better in Bandpass
> filtered
>                 THR_SIG1 = 0.5*(THR_SIG1);
>                 %THR_NOISE1 = 0.5*(THR_SIG1);
>
>         else
>             m_selected_RR = mean_RR; %the latest regular beats mean
>         end
>
>     end
>
>       %% calculate the mean of the last 8 R waves to make sure that QRS is
> not
>        % missing(If no R detected , trigger a search back) 1.66*mean
>
>        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(end)) >= round(1.66*test_m)% it shows a QRS
> is missed
>               [pks_temp,locs_temp] = max(ecg_m(qrs_i(end)+
> round(0.200*fs):locs(i)-round(0.200*fs))); % search back and locate the max
> in this interval
>               locs_temp = qrs_i(end)+ round(0.200*fs) + locs_temp -1;
> %location
>
>               if pks_temp > THR_NOISE
>                qrs_c = [qrs_c pks_temp];
>                qrs_i = [qrs_i locs_temp];
>
>                % find the location 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
>                % take care of bandpass signal threshold
>                if y_i_t > THR_NOISE1
>
>                       qrs_i_raw = [qrs_i_raw locs_temp-round(0.150*fs)+
> (x_i_t - 1)];% save index of bandpass
>                       qrs_amp_raw =[qrs_amp_raw 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 a QRS candidate occurs within 360ms of the previous
> QRS
>                  % ,the algorithm determines if its T wave or QRS
>                  if length(qrs_c) >= 3
>                       if (locs(i)-qrs_i(end)) <= 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(end)-round(0.075*fs):qrs_i(end)))); %mean slope of
> previous R wave
>                              if abs(Slope1) <= abs(0.5*(Slope2))  % slope
> less then 0.5 of previous R
>                                  nois_c = [nois_c pks(i)];
>                                  nois_i = [nois_i locs(i)];
>                                  skip = 1; % T wave identification
>                                  % adjust noise level in both filtered and
>                                  % MVI
>                                  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
>
>         if skip == 0  % skip is 1 when a T wave is detected
>         qrs_c = [qrs_c pks(i)];
>         qrs_i = [qrs_i locs(i)];
>
>         % bandpass filter check threshold
>          if y_i >= THR_SIG1
>                         if ser_back
>                            qrs_i_raw = [qrs_i_raw x_i];  % save index of
> bandpass
>                         else
>                            qrs_i_raw = [qrs_i_raw locs(i)-round(0.150*fs)+
> (x_i - 1)];% save index of bandpass
>                         end
>                            qrs_amp_raw =[qrs_amp_raw y_i];% save amplitude
> of bandpass
>           SIG_LEV1 = 0.125*y_i + 0.875*SIG_LEV1;% adjust threshold for
> bandpass filtered sig
>          end
>
>         % adjust Signal level
>         SIG_LEV = 0.125*pks(i) + 0.875*SIG_LEV ;
>         end
>
>
>     elseif THR_NOISE <= pks(i) && pks(i)<THR_SIG
>
>          %adjust Noise level in filtered sig
>          NOISE_LEV1 = 0.125*y_i + 0.875*NOISE_LEV1;
>          %adjust Noise level in MVI
>          NOISE_LEV = 0.125*pks(i) + 0.875*NOISE_LEV;
>
>
>
>     elseif pks(i) < THR_NOISE
>         nois_c = [nois_c pks(i)];
>         nois_i = [nois_i locs(i)];
>
>         % noise level in filtered signal
>         NOISE_LEV1 = 0.125*y_i + 0.875*NOISE_LEV1;
>         %end
>
>          %adjust Noise level in MVI
>         NOISE_LEV = 0.125*pks(i) + 0.875*NOISE_LEV;
>
>
>     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 = [SIGL_buf SIG_LEV];
> NOISL_buf = [NOISL_buf NOISE_LEV];
> THRS_buf = [THRS_buf THR_SIG];
>
> % take a track of thresholds of filtered signal
> SIGL_buf1 = [SIGL_buf1 SIG_LEV1];
> NOISL_buf1 = [NOISL_buf1 NOISE_LEV1];
> THRS_buf1 = [THRS_buf1 THR_SIG1];
>
>
>
>
>  skip = 0; %reset parameters
>  not_nois = 0; %reset parameters
>  ser_back = 0;  %reset bandpass param
> end
>
> 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 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
> ##############
>
> Regards
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



More information about the R-help mailing list