How to index equally spaced chunks from a long signal?

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)))

Answer 1

[David Hill]

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));

Answer 2

[Benjamin Thompson]

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

>>