Converting Raw Data to Simple Charts

[sleepyhobbit]

I have the Muse S (Gen 2). I used the Mind Monitor app to record 15 minutes of brainwaves (while I was using the computer). I sent the recording to DropBox and then opened the raw data in Excel. After removing the blank rows and creating averages for each type of brainwave (Delta, Theta, etc.), I generated the chart below. My chart seems pretty chaotic (ugly) compared to some of the other charts I've seen people upload on this forum, so I'm looking for tips. Is it unusual to see so much variance, or is second-by-second data generally messy? Perhaps my device is generating a lot of noise or interference, but the sensor-specific portion of the Mind Monitor app shows pretty "flat" lines (i.e. low noise). I was thinking about "collapsing" my data (or smoothing the curves) by averaging the second-level data into minute-level data. Was wondering if anyone else has tried this approach and if it is appropriate for EEG data. Thanks!

Brainwaves_chart_rawdata.jpg (243.53 KiB) Viewed 1909 times

[James]

Excel isn't so good when you have a lot of data points.
Try the online charts: https://mind-monitor.com/Chart.php

[sleepyhobbit]

Hi James. Thanks for the quick response. And thanks for creating so many helpful tools. It looks like your online wizard converts the second-level data to minute-level data, which is exactly what I needed. The chart now looks 1,000x better (see below). Thank you!!

smoothed_chart.png (77.12 KiB) Viewed 1896 times

[James]

You can also click "All Data Points" if you want a more messy looking chart

[sleepyhobbit]

Haha. Yes, I saw that option. The smoother chart is much easier to read. Thanks again!

[sleepyhobbit]

Hi James. Sorry. Quick follow-up question regarding the charting tool (https://mind-monitor.com/Chart.php).

What do the "C" and "D" markers on the chart mean?

BF = Bad fit
GF = Good fit
J = Jaw clench
C = ?
D = ?

Thanks!

[James]

Connected and Disconnected.
If you hover over a marker with the mouse it will tell you what it is.

[sleepyhobbit]

Thank you!