Mind Monitor

Wow! Amazing news!! I currently have the Muse 1 and am eagerly awaiting the Muse S Gen 2 which I just ordered - I will try this as soon as I get it. Thank you, thank you, THANK YOU for all of your work!!!

Hi James! Again huge thanks for this super helpful app! The possibilities are endless.

As you directed, I tapped "MindMonitor" 10X in the iPhone app and now I see my Pulse data streaming in the live graph (Amazing). But I can't find it in the OSC stream or in the the saved CSV file. Is there something I need to turn on in settings?

If you're seeing the PPG data in the live view, then it will be in the OSC and CSV data for sure.
After you enable the setting, you need to disconnect and reconnect the Muse to see the PPG stuff show up, but after that, it's just enabled.
The PPG OSC will show as muse/ppg fff.
The online charts are not set up to show PPG yet, but you'll see the data in the actual CSV data.

Thanks! I am getting ppg data now in both the OSC stream and the CSV file. I see the three columns are helpfully labeled "PPG Ambient", "PPG IR", and "PPG Red"... is there a quick/easy way to concert this to heart rate (BPM)? (Sorry, this is probably a simple question!)

No, it's a massive pain to convert to heart rate and I don't have a good algorythm for it yet. This is why it's all hidden under the secret menu.
If you can figure out a good algorythm that is stable when the head moves in different lighting conditions, then please let me know!

Actually, I see that "Heart_Rate" is already a column in the CSV file - so how is that calculated? And why can't that be streamed live via OSC?

I have been graphing the PPG data from the CSV files and I am confused about why the "Ambient" value fluctuates so much: I assumed that meant ambient lighting, which would mean that you could use it to establish the baseline even under changing lighting conditions, but it must mean some other kind of "ambience" because it changes just like the IR and Red columns.... To find the BPM, I guess you would need a peak-finding algorithm that frequently adjusts the baseline (and also throws out crazy outliers). But I am out of my depth here, sorry! Wish I could be helpful!!

I have peak-finding algorithm that sort-of works. That's what you're seeing in the live data. I've not included it in the OSC data, as it's kinda junky at the moment. It has some basic DSP in there to clean up the signal, but it's not robust enough yet for me to be happy releasing it in to the wild. My hopes at making this data publicly available was that someone out there would have a better idea than me about an algorithm

Hi!
It's been mentioned this is available on iPhones. I can't yet see it on my Android version. Would it please be possible to make this hidden update available to Android users, too? I am a PhD researcher using Muse and being able to do it on my phone with everything including PPG would be a godsend. Many thanks!
- Marco

P.S. For future reference, what is your preferred way to cite the Mind Monitor?

@James - I've been thinking about peak finding algorithms for the heart rate monitor, and I was wondering if you'd considered a totally different approach and doing an Fast Fourier transform? Or a power spectral density function? (Wish I could help with actual coding, sorry!)

@James - Thank you! You have done a wonderful job with this app supporting a diverse and vibrant community to do research and develop skills. I am also very keen on solving the raw PPG to BPM problem. Any updates on that front? How could we help you?