InIn the attached code, all starts of the peak is getting detected. From this how to filter out dicrotic notch and valley?

LD = load('C:\Users\ANU\Desktop\TBME2013-PPGRR-Benchmark_R3\data\0009_8min.mat.mat')

% remove first trough:

ppg = LD.signal.pleth.y;

ppg(1:10) = [];

% indentify all peaks

[all_peak_value,all_peak_location]= findpeaks(ppg);

% identify all troughs in data

[all_trough_value,all_trough_location]= findpeaks(-ppg);

all_trough_value = -all_trough_value;

% identify main peak (i.e. ones lower than 5)

[main_trough_value,main_trough_location]= findpeaks(ppg,'MinPeakProminence',5);

counter = 0;

for i = 1:length(main_trough_location)

%c=[];

start=main_trough_location(i)-100;

ending=main_trough_location(i);

%c= (all_trough_location>start & all_trough_location<ending);

%c1=c(end);

[r,c] = find(all_trough_location>start & all_trough_location<ending);

end

figure

plot(ppg,'r')

hold on

plot(all_trough_location,all_trough_value,'ko')

Answer 1

[Aditya Srikar]

Hi Anupama,

You can use high pass filter to remove low frequency tones. Through this, you can filter out dicrotic notch and valleys.

A high-pass filter attenuates signals below a cutoff frequency (the stopband) and allows signals above the cutoff frequency (the passband). The amount of attenuation depends on the design of the filter.

For more details, look at the following documentation.

https://in.mathworks.com/help/signal/ref/highpass.html

Hope it helps !