hello
IMHO, you don't need the peaks code (and the for loop) to make the low amplitude signals to zero
you can do it directly on the raw signal
then I added a new portion of code to detect the flat sections that are longer than min_contiguous_samples contiguous samples
so you can also discard if needed the short ones
see the demo below :
load data.mat;
x=1:numel(data);
y=data;
z = y;
thresh = 0.05; % height threshold
%% your for loop simplified :
ind = abs(z) < thresh; % NB we need ind in the new code below
z(ind) = 0;
%% new code
min_contiguous_samples = 300; % select segments only if they are at least this length => detect signal = 1
detect_signal = zeros(size(x))+0.5; % initialisation
% now define start en end point of segments above threshold
%%%%%%%%%%
% This locates the beginning /ending points of data groups
D = diff([0;ind;0]);
begin = find(D == 1);
ends = find(D == -1) - 1;
%%%%%%%%%%
length_ind = ends - begin;
ind2= length_ind>min_contiguous_samples; % check if their length is valid (above min_contiguous_samples value)
begin = begin(ind2); % selected points
ends = ends(ind2); % selected points
x2 = x(ind);
y2 = y(ind);
% define the begin / ending x, y values of raw data
x2_begin = x(begin);
y_begin = interp1(x,y,x2_begin);
x2_ends = x(ends);
y_ends = interp1(x,y,x2_ends);
for ci = 1:length(begin)
ind = (x>=x2_begin(ci) & x<=x2_ends(ci));
detect_signal(ind) = 1;
end
% plot
plot(x,y,x,z,x,detect_signal);xlim([2 2.3]*1e5);ylim([-1.5 1.5]);
legend('original signal','modified signal','flat sections detected')
