Separate windows signal and peak detection

3 次查看（过去 30 天）

Ilan Moshe 2021-5-30

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/843635-separate-windows-signal-and-peak-detection

编辑： Image Analyst 2021-7-5

Hello,

In the below picture, I have to detect each window, where each augmentation of the signal represents an air inspiration. So, it's important to separate each window in order to get an accurate breath rate.

%data_blue{i}.meanBlueLevels  --> Original signal (subplot(2,1,1))
data_filter=lowpass(data_blue{i}.meanBlueLevels,0.1,Fs);
data_filter=data_filter.^2;
t=1:length(data_blue{i}.meanBlueLevels);
subplot(2,1,1)
plot(t,data_blue{i}.meanBlueLevels)
subplot(2,1,2)
plot(t,data_filter)

I tried to use the built function envelope with the 'peak' parameter, but I think it will be not have enough robustness ... (I should avoid using of any threshold.)

Any help is much appreciated. Thank you.

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

回答（2 个）

Image Analyst 2021-5-30

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/843635-separate-windows-signal-and-peak-detection#answer_712740

编辑：Image Analyst 2021-5-30

在 MATLAB Online 中打开

Attach your data. What if you just threshold? Why do you refuse to use a threshold? It looks like it would work well.

itsABreath = signal > 1; % Or whatever value works.

This will be true if the signal is more than 1 and false if it's less than 1.

If you have the Image Processing Toolbox, you can label each breath and then use regionprops(), or ismember() and find(), to find the starting and stopping index of each breath.

We've seen this before with audio signals and people wanted to determine the voiced and silent parts of the audio recording so you might search for silent, silence, voice, words, and things like that.