Exercise #3 (4.2.2015) Electrocardiography (ECG) BEFORE the

Exercise #3 (4.2.2015)
Electrocardiography (ECG)
BEFORE the exercise:
1. Read the article by Chern-Pin Chua et al.
Chern-Pin Chua et al. Heart Rate Variability Can Be Used to Estimate Sleepiness-related
Decrements in Psychomotor Vigilance during Total Sleep Deprivation Sleep
2. Bring the article by Chern-Pin Chua et al. to the exercise session
3. Familiarize yourself with the tasks below
4. Bring a laptop with Matlab (if possible)
EXERCISE session:
* Divide into two groups, distribute work evenly, help the other group if needed.
* You will get a mark of attendance when both groups have completed the exercise.
Measurements (Part I, approximately 45 minutes):
5. Start the ECG measurement program (on Aino’s laptops)
6. Synchronize the measurement devise with the laptop.
7. Perform three 10-minute ECG measurements1
a. Follow Chern-Pin Chua et al.
b. Use subject numbers (no names!) to (re)name the files
c. Fail one measurement on purpose (e.g. raise the pulse by running in place, touch the
8. Move the data to laptops with Matlab, share data with the other group
Analysis (Part II, approximately 40 minutes):
9. Load the data files (4 ok, 2 failed) in Matlab (ask the assistant for help if needed)
10. Filter the ECG data as in Chern-Pin Chua et al.
11. Plot the ECG data. How does the failed measurements look like compared to the successful
12. Find the ECG peaks (choose the method).
13. Calculate and plot the RR-intervals against measurement time. Do the plots resemble the “Wellrested” or “Sleep-deprived” group (Chern-Pin Chua et al. Fig. 2.)?
14. Calculate the SDNN. Are they as in Chern-Pin Chua et al.?
15. Calculate the average pulse during the 10 minute measurement. What is the normal range?
Wrap up (Part III, approximately 5 minutes):
16. Compare results with the other group: did both groups arrive at the same result? If not,
When you volunteer for a measurement, remember that the data will be available to the others.