1. Principals of Digital Signal Recording

2. How do we represent a continuously variable signal digitally? Sampling – Sampling rate – number of measurements per unit time – Sampling depth or quantization – number of gradations by which the measurement can be recorded

3. How do we represent a continuously variable signal digitally? Sampling – What would be the advantage to higher sampling rates?

4. How do we represent a continuously variable signal digitally? Sampling – What would be the advantage to higher sampling rates? Nyquist limit

5. How do we represent a continuously variable signal digitally? Sampling – What would be the advantage to higher sampling rates? Nyquist limit Aliasing – What would be the disadvantage? Data size Compute time

6. How do we represent a continuously variable signal digitally? Sampling – What would be the advantage to greater sampling depth? Finer resolution – What would be the disadvantage? Data size Possibly compute time

7. How do we represent a continuously variable signal digitally? Sampling – A note about data size and compute time: New data size = increase in quantization x number of samples x number of electrodes!

8. Filters used in EEG

9. What is a filter?

10. Filters let some “stuff” through and keep other “stuff” from getting through – What do we want to let through? – What do we want to filter out?

11. What is a filter? The goal of filtering is to improve the signal to noise ratio – Can the filter add signal?

12. Different Kinds of Filters Low-Pass (High-Cut-Off) High-Pass (Low-Cut-Off) Band-Pass Notch Each of these will have a certain “slope”

13. How do Filters Work? Notionally: – Transform to frequency domain – Mask some parts of the spectrum – Transform back to time domain

14. Are There Any Drawbacks? Yes Filters necessarily distort data – Amplitude distortion – Latency distortion Forward/backward/zero-phase

15. Recommendations Should you filter? – Yes, when necessary to reveal a real signal Problem: how do you know it’s “real” – No, always look at the unfiltered data first What filters should you use? – Depends on your situation (e.g. what EEG band are you interested in? Do you have 60Hz line noise?) – General rule: less aggressive filters are less distorting