with the $360Hz$ sampling rate. Run your algorithm for ECG data given in

data.mat. Additionally, add artificial noise to the data and check the robustness

of your algorithm to noise. You will hand in a report and all files related to

your code $($functions$,$ m$-$file, data etc.$).$

Solve the following problems and add the results to your report. The report

should include every plot requested in the problems. Make sure to add titles

to your plots.

Plot the first $15s$ of raw ECG data.

You must use the filters for implementation of following steps.

Plot heartrate $($in bpm$)$ as a function of time.

Number of QRS complexes between $20$min and $25$min $($print on command

window$).$

Add random noise $($between $-0\mathrm{.}5$ and $0\mathrm{.}5)$ to the original data and repeat

steps $1-4.$

Plot all of the results for each step in your algorithm using subplots and

add them to the report.

Also report should include flowchart and detailed explanation for your

algorithm.

Discuss the effectiveness of your algorithm by comparing real ECG data

and noisy ECG data results.