The Zeo Bedside unit has a serial port which emits the raw signal it picks up from your forehead, the brainwaves; Delta, Theta, Alpha, Beta 1, Beta 2, Beta 3 and Gamma, the sensor impedance and also the 30 second sleep stages. How do you get this data?
1) Make a cable
2) Get and install a "Real time" firmware upgrade into the Zeo Bedside unit.
3) Get ZeoScope (free)
--------------------
The Cable
The Zeo Bedside's serial port can be connected to your PC using a Serial -to- USB cable, but Zeo does not sell one and if you want the data, you must make it. The cable itself is a RS-232 Serial to USB, so there's a chip in the USB
connector thus one cannot use a standard USB cable and "hack it up". To make mine I
followed the directions here:
http://www.sleepstreamonline.com/rdl/starting.html
To make it, I got these parts:
http://www.mouser.com/Search/ProductDet ... 16-02-1114
(5 each, to have a couple spares, they are cheap... wire termination connector clip thingys)
http://www.mouser.com/Search/ProductDet ... 50-57-9405
(1 each the plastic 5 pin connector)
http://www.mouser.com/Search/ProductDet ... 32R-3V3-WE
(1 each, $20... the cable itself)
--------------------
The Firmware Upgrade
It's explained step by step at the same web page on how to make the cable:
http://www.sleepstreamonline.com/rdl/starting.html
--------------------
ZeoScope
ZeoScope is PC software available for free here:
http://www.github.com/dancodru/ZeoScope
Have fun watching your brainwaves streaming by... Look left, look right, watch the wave patterns. Take off the Zeo headband and press it against your chest... WOO... One of the weirdest EKG's you've ever seen. :)
Showing posts with label Brainwaves. Show all posts
Showing posts with label Brainwaves. Show all posts
Monday, March 19, 2012
Wednesday, February 22, 2012
Clustering Zeo Brainwaves
One reason "sleep stages" exist is so one can quantify how much time was spent in what kind of sleep. It is a multiple level discrete classification of what in reality is a continuous process, but none the less the concept of "sleep stages" is useful. I would like to identify the nature of my sleep and associate how I feel the next day based on how much of what kind of sleep I had. If I can identify and count the duration of different kinds of sleep I might be able to
correlate that with how I feel, hence I could then get a handle on
sleep quality. People say the more "Deep" and "REM" you get the better,
but I'm guessing there's more to that story.
The challenge I have is that I only have a Zeo, which is a 3 lead frontal lobe EEG non-medical device and I get a bit confused on how sleep is categorized based on the dominance of this wave or that. This is compounded by each person being different and I read today that Obstructive Sleep Apnea (OSA) persons have somewhat abnormal sleep as well. I could use Zeo's classification of sleep stages (I might, I have them in real-time) or I could come up with my own scheme. In this adventure, I going to make my own.
I have Zeo brainwaves (Delta, Alpha, Betas, Theta, Gamma) and sleep stages (Wake, REM, Light, Deep) gathered via a serial port from the Zeo Bedside unit archived in real-time to a historian. I can extract the data between one date/time and another such as a night's sleep. Last night's data looks like this:
Now, I'm no expert in sleep stages, but I am one in data analysis and I see a few different forms of sleep. For this adventure I'm not going to try to identify the sleep stages using the established medical definitions (if it is even possible with the Zeo), but I'm going to let the data itself decide what it sees. How am I going to do this?
Clustering
Clustering is a data method that separates data into "piles" (clusters) based on their similarities and differences. In this case the software looks at each moment in time and decides if the Delta, Alpha, Betas, Theta, Gamma wave values (amplitudes) are similar to all the other cases. In this exercise I took noise out of the data by taking 30-45 second averages of the data (just a double-click in our software). Then using a "Self Organizing Map" (SOM), I group the data based on its similarity. SOM's use a process that moves similar data towards each other, and dissimilar data away from each other, on a two dimensional map. That way I can take the 7 wave forms (7 dimensional data) and project it on a 2D surface, like moving chips around on a table, putting similar ones together automatically. We humans can think in 2D and 3D pretty good. 7D is very difficult for us mere mortals. What you get after the SOM groups the data is something that looks like this:
Very pretty. Rather impressive. Good to have on your desktop when the boss walks by if you are a data analysis person (wink). Each square has very similar data within it and neighboring squares also have data with similar characteristics. The closer the squares, the closer the values. Adjacent red regions contain very similar values. The green, yellow and blue indicate larger differences, like mountains or valleys between the red regions. I can group these squares (and the data within them) into clusters of similar data by setting a "data distance" (dissimilarity) criteria. Below you can see 5 different gray regions (clusters) each of which contain similar data.
OK, so what, you ask? Well, I can then export out the members (rows of data) of those clusters and their cluster number. That cluster number is very similar in concept as a sleep stage and look at what it shows us...
At the very bottom you can see the blue line that is our "home-made" Sleep Stages but in a different numbering scheme, independent of any medical professional, based on my personal data. In comparing the cluster number to the Zeo's sleep stages I can see it is somewhat similar to what the Zeo indicates, but I also see that my scheme identifies the character of the data better, because the Zeo is trying to conform to medical definitions where mine conforms reality.
The blue line is actually smoothed with a simple algorithm that says if the current row of data is uncategorized (not in a cluster) then presume it to be in the just-prior cluster. That's not perfect, but a pretty good assumption on a real-time continuous process like the brain. Doing this type of post-processing helps reduce the noise in our new "Sleep Stage".
Next Steps
I can run this clustering "model" in real time with the wave data coming in and auto-assigned to my custom sleep stages and either in real time or after I wake up I can count how much time I slept in what type of sleep. I can use this, or the Zeo's sleep stages, or both to hopefully correlate that with how I feel the next day, and also correlate it with what I did before to get such sleep. We'll see about that in future posts.
The challenge I have is that I only have a Zeo, which is a 3 lead frontal lobe EEG non-medical device and I get a bit confused on how sleep is categorized based on the dominance of this wave or that. This is compounded by each person being different and I read today that Obstructive Sleep Apnea (OSA) persons have somewhat abnormal sleep as well. I could use Zeo's classification of sleep stages (I might, I have them in real-time) or I could come up with my own scheme. In this adventure, I going to make my own.
I have Zeo brainwaves (Delta, Alpha, Betas, Theta, Gamma) and sleep stages (Wake, REM, Light, Deep) gathered via a serial port from the Zeo Bedside unit archived in real-time to a historian. I can extract the data between one date/time and another such as a night's sleep. Last night's data looks like this:
Now, I'm no expert in sleep stages, but I am one in data analysis and I see a few different forms of sleep. For this adventure I'm not going to try to identify the sleep stages using the established medical definitions (if it is even possible with the Zeo), but I'm going to let the data itself decide what it sees. How am I going to do this?
Clustering
Clustering is a data method that separates data into "piles" (clusters) based on their similarities and differences. In this case the software looks at each moment in time and decides if the Delta, Alpha, Betas, Theta, Gamma wave values (amplitudes) are similar to all the other cases. In this exercise I took noise out of the data by taking 30-45 second averages of the data (just a double-click in our software). Then using a "Self Organizing Map" (SOM), I group the data based on its similarity. SOM's use a process that moves similar data towards each other, and dissimilar data away from each other, on a two dimensional map. That way I can take the 7 wave forms (7 dimensional data) and project it on a 2D surface, like moving chips around on a table, putting similar ones together automatically. We humans can think in 2D and 3D pretty good. 7D is very difficult for us mere mortals. What you get after the SOM groups the data is something that looks like this:
Very pretty. Rather impressive. Good to have on your desktop when the boss walks by if you are a data analysis person (wink). Each square has very similar data within it and neighboring squares also have data with similar characteristics. The closer the squares, the closer the values. Adjacent red regions contain very similar values. The green, yellow and blue indicate larger differences, like mountains or valleys between the red regions. I can group these squares (and the data within them) into clusters of similar data by setting a "data distance" (dissimilarity) criteria. Below you can see 5 different gray regions (clusters) each of which contain similar data.
OK, so what, you ask? Well, I can then export out the members (rows of data) of those clusters and their cluster number. That cluster number is very similar in concept as a sleep stage and look at what it shows us...
At the very bottom you can see the blue line that is our "home-made" Sleep Stages but in a different numbering scheme, independent of any medical professional, based on my personal data. In comparing the cluster number to the Zeo's sleep stages I can see it is somewhat similar to what the Zeo indicates, but I also see that my scheme identifies the character of the data better, because the Zeo is trying to conform to medical definitions where mine conforms reality.
The blue line is actually smoothed with a simple algorithm that says if the current row of data is uncategorized (not in a cluster) then presume it to be in the just-prior cluster. That's not perfect, but a pretty good assumption on a real-time continuous process like the brain. Doing this type of post-processing helps reduce the noise in our new "Sleep Stage".
Next Steps
I can run this clustering "model" in real time with the wave data coming in and auto-assigned to my custom sleep stages and either in real time or after I wake up I can count how much time I slept in what type of sleep. I can use this, or the Zeo's sleep stages, or both to hopefully correlate that with how I feel the next day, and also correlate it with what I did before to get such sleep. We'll see about that in future posts.
Wednesday, February 1, 2012
Strange REM
As I continue to prepare for doing some experiments (more on that in the next post) I had some strange brainwaves during my first REM period last night. Check out the chart below:
This is an image of the various frequencies streaming real-time out of the Zeo into our software during the period of interest in my sleep last night. The first section that looks domed, or a "fish eye" as I call it, is deep sleep, then comes the REM period, then another period of deep. During the REM period there is some fairly regular Delta spikes while other brainwave frequencies dip. I have not seen this before. I do vaguely remember dreaming, something about "discovering cosmic rays in my brainwaves". Funny-odd that I would dream about my brainwaves when in fact my brainwaves are doing something odd. The spikes are not related to movement or waking. I had an IR cam on me and I stepped through the frames. There was a few movements during the time, but not at all at the times of the spikes or even having any regularity associated with them. I probably had some arousal during the time, else I would probably not remember the "cosmic rays" thing.
The other thing that was odd last night is that I slept only 4 hours and awoke fairly refreshed and could sleep no longer. I did have a "power nap" during the day before and I did not take any sleep aids before going to bed. There's an interesting decrease in the depth and duration of deep sleep that goes on during my sleep cycles that I notice and when the deep cycles diminish to near nothing, I notice I awaken. More on that in another post.
(click for a bigger picture)
This is an image of the various frequencies streaming real-time out of the Zeo into our software during the period of interest in my sleep last night. The first section that looks domed, or a "fish eye" as I call it, is deep sleep, then comes the REM period, then another period of deep. During the REM period there is some fairly regular Delta spikes while other brainwave frequencies dip. I have not seen this before. I do vaguely remember dreaming, something about "discovering cosmic rays in my brainwaves". Funny-odd that I would dream about my brainwaves when in fact my brainwaves are doing something odd. The spikes are not related to movement or waking. I had an IR cam on me and I stepped through the frames. There was a few movements during the time, but not at all at the times of the spikes or even having any regularity associated with them. I probably had some arousal during the time, else I would probably not remember the "cosmic rays" thing.
The other thing that was odd last night is that I slept only 4 hours and awoke fairly refreshed and could sleep no longer. I did have a "power nap" during the day before and I did not take any sleep aids before going to bed. There's an interesting decrease in the depth and duration of deep sleep that goes on during my sleep cycles that I notice and when the deep cycles diminish to near nothing, I notice I awaken. More on that in another post.
Saturday, January 28, 2012
An Unusual Night
Last night is noteworthy because it was unusual. Below you see an annotated chart showing the ResMed data (top chart), Pulse-Ox and Zeo brain waves (middle chart) and at the very bottom, the Zeo 5 minute sleep stages from the Zeo web site. The "night" was unusual because I had some sort of metabolical "issue" at the beginning, then fell asleep for a while without my ResMed nor pulse-oximeter on, then woke up and put them on and went back to sleep.
The numbers with circles are some interesting points:
1. Before all this I think I had a "hypoglycemic" (diabetic type) episode. I'm not diabetic, but I felt very strange, broke out in a sweat, felt "minty sweaty" all over my body and very light headed, almost passing out (buzzzz). It was like I had food poisoning and was going to "pay the price". I also felt hypotensive so I checked my blood pressure but it was normal. I became very thirsty and craved sugar. I drank a large glass of water and a bunch of Oreos and started feeling better. Strange.
2. After all those Oreo cookies, I felt sleepy and laid down. I fell asleep for about 3 hours without my xPAP. I think I was probably snoring pretty good. Oops. Not proper therapy.
3. I woke up at 12:30 AM, did this-n-that for about 45 minutes, then put on the pulse-oximeter and went to sleep again with the ResMed.
4. About 2 hours into that sleep, I can see in my data I had a cluster of apneas and some distress (breathing with some "excitement"). During this time I de-sated to 86% due to not only long duration apneas, but many in succession.
5. I notice in my Zeo brain wave data that the deeper sleep "fish eyes" that form in my brain waves are more pronounced during my untreated "nap" than during my "sleep". I think it was because I had gotten that deeper rest first, then later I didn't need it so much. Just a theory, because every night I see those deep sleep "fish eyes" progressively get smaller during the night, so this fits here as well.
6. You can see from the brainwaves that I was getting sleepy, that on-set was coming even though I was still awake. The waves were converging.
Just an odd night and it is interesting to me to see what was going on.
The numbers with circles are some interesting points:
(Click for a bigger image)
1. Before all this I think I had a "hypoglycemic" (diabetic type) episode. I'm not diabetic, but I felt very strange, broke out in a sweat, felt "minty sweaty" all over my body and very light headed, almost passing out (buzzzz). It was like I had food poisoning and was going to "pay the price". I also felt hypotensive so I checked my blood pressure but it was normal. I became very thirsty and craved sugar. I drank a large glass of water and a bunch of Oreos and started feeling better. Strange.
2. After all those Oreo cookies, I felt sleepy and laid down. I fell asleep for about 3 hours without my xPAP. I think I was probably snoring pretty good. Oops. Not proper therapy.
3. I woke up at 12:30 AM, did this-n-that for about 45 minutes, then put on the pulse-oximeter and went to sleep again with the ResMed.
4. About 2 hours into that sleep, I can see in my data I had a cluster of apneas and some distress (breathing with some "excitement"). During this time I de-sated to 86% due to not only long duration apneas, but many in succession.
5. I notice in my Zeo brain wave data that the deeper sleep "fish eyes" that form in my brain waves are more pronounced during my untreated "nap" than during my "sleep". I think it was because I had gotten that deeper rest first, then later I didn't need it so much. Just a theory, because every night I see those deep sleep "fish eyes" progressively get smaller during the night, so this fits here as well.
6. You can see from the brainwaves that I was getting sleepy, that on-set was coming even though I was still awake. The waves were converging.
Just an odd night and it is interesting to me to see what was going on.
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