How to index equally spaced chunks from a long signal?
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I have a long signal that includes 120 stimulation pulses evenly spaced. I have the indices of these pulses and I want to find the mean of the signal from 5-7 ms after each pulse to use as a baseline value. Currently, I am extracting individual pulses and able to find the mean of this time period from individual pulses, but how can I find the mean from all of them at once?
for b = 1:numPulses
windowBefore = round(0.001*db1.Fs);
windowAfter = round(0.05*db1.Fs);
window1 = -windowBefore:windowAfter;
windowSelected = window1 + pulseIndexes(b);
signal = db1.emg(windowSelected,d);
m = mean(signal(ceil(Fs*0.005):ceil(Fs*0.007)))
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David Hill
2022 年 2 月 14 日
編集済み: David Hill
2022 年 2 月 14 日
ms5=1000;%approximate number of data samples after the pulse to start averaging on (should be based on your sample frequency)
ms7=1400;%approximate number of data samples after the pulse to stop averaging on (should be based on your sample frequency)
m=arrayfun(@(x)mean(yourData(indexOfPulses(x)+ms5:indexOfPulses(x)+ms7)),1:numel(indexOfPulses));
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Benjamin Thompson
2022 年 2 月 14 日
If you can define an index vector with ones in the positions where you want to calculate the mean, then you can use the index vector to pass a smaller subset of your data to the mean function. For example, to get the mean of all samples exceeding 1 in a sinusoid of frequency 2, amplitude 2 ,for 5 seconds:
>> t = 0:0.01:5;
>> x = 2*sin(2*pi*2*t);
>> figure, plot(t, x)
>> Ipulse = x > 1;
>> mean(x(Ipulse))
ans =
1.6808
>>
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