Hi Fahmida, you must first upsample the lower sampling rate signal to match the other signal's frequency, and then you use Matlab's 'xcorr' function which computes the cross-correlation between the two signals.

Here is a good example of using cross-correlation to align two signals:

https://uk.mathworks.com/help/signal/ug/align-signals-using-cross-correlation.html

Dear Fahmida Haque , please refer to this example reporting how to measure signal similarities. It will help you answer questions such as: How do I compare signals with different lengths or different sampling rates? How do I find if there is a signal or just noise in a measurement? Are two signals related? How to measure a delay between two signals (and how do I align them)? How do I compare the frequency content of two signals? Similarities can also be found in different sections of a signal to determine if a signal is periodic. Link: https://fr.mathworks.com/help/signal/examples/measuring-signal-similarities.html

https://fr.mathworks.com/matlabcentral/answers/321223-cross-correlation-issue-how-can-i-align-two-signals

Dear Fahmida,

1- you can up-sample the lower frequency or down-sample the higher one.

2- you can use 1-D data interpolation .

If the two bio signals are correlated, find a flag or feature shared between them to help you synchronize the signals. After that down sample the high frequency signal by the half and you are done.

There are a few things that need to be figured out before synchronizing them. Does both the system start acquiring data at the same time or is there a difference? If they do not start acquiring at the same time, there need to be a digital flag in both the signals as mentioned by Mohamed Mabrouk If any of the condition is not met, I am unsure how precise will be synchrony method.