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 Zeo. Show all posts
Showing posts with label Zeo. Show all posts
Monday, March 19, 2012
Saturday, February 25, 2012
Zeo Sleep Score: Mean Anything?
The Zeo puts out a sleep score based on hours slept, the amount of time in REM and Deep sleep and the number and duration of waking during the night. Does this have any bearing on how you feel or perform, really? In some initial data collection, the answer is YES.
From time to time I do a home-made "Whack-A-Mole" type of measurement of response time. In this little performance game an image appears in random locations 10 times in a window and I must mouse to the image and click on it. The average time it takes between clicks is logged each time I play the game.
If I do a chart of my Zeo Sleep Score vs. my response time it looks like this:
You can see when my Zeo Sleep Score is low, my response time is high (I'm slower to respond) and the reverse is true. Mathematically the correlation is low, but to our eyes we can see there is a relationship between these two independently arrived at metrics.
From time to time I do a home-made "Whack-A-Mole" type of measurement of response time. In this little performance game an image appears in random locations 10 times in a window and I must mouse to the image and click on it. The average time it takes between clicks is logged each time I play the game.
If I do a chart of my Zeo Sleep Score vs. my response time it looks like this:
You can see when my Zeo Sleep Score is low, my response time is high (I'm slower to respond) and the reverse is true. Mathematically the correlation is low, but to our eyes we can see there is a relationship between these two independently arrived at metrics.
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
Still Preparing: Events
I'm still preparing for having all the data I need / want. I have the Zeo's brainwaves in real-time, Contec CMS 50E post-sleep (which is fine getting it after the fact for now) and the ResMed S9 AutoSet data post-sleep (I don't know how to get it real-time, tho it has a serial port). So, for the real-time time series I'm in pretty good shape. However, I need to track various "events".
Events
An event is something that occurs at a time and generally has a start-time, end-time and duration. Having any two allows you to calculate the third automatically. So we put an "Event" object into our software and put them to use because I have events from the ResMed S9 AutoSet; hypopneas, obstructive apneas, central apneas and recording start events. In ResMed terms, the apneas have an end-time and duration because they are determined after the fact, and the recording start event is instantaneous: the start-time only. These are already gathered and stored in our real-time historian with the ResMed data collection we do. This is spiffy because our software has multiple tasks, an spO2 and ResMed file watcher watching a directory and when I've gathered the files I just drag and drop them into that folder where they are "sucked up" and the data is put into the real-time database and the original files are automatically archived for back-up purposes. OK, I'm getting off topic...
I need to add my own events too, such as periods of time I feel groggy, or really good, or something else of merit that should be recorded.
Doses
A close cousin to an event is what I call a "Dose". This is an event like activity (has a time and maybe a duration) that has a quantity associated with it. I call it a Dose because it's like taking a medicine. "I took X mg of Y drug at Z time", or I just drank a full pot of coffee at this time. Even exercise is like a dose, "I averaged an aerobic heart rate of X from this time to that time". Having these events, time stamped, with quantities, gives me information about how much, how long before sleep-onset they occurred, or totaled during the day. This way I can log that I had a pound of steak for dinner, or took two Excedrin at 10 PM or had an hour of "this strenuous" exercise at 2 PM or 1 cup of Tulsi Tea 10 minutes before bed, etc.
Once I have these Events and Doses, and a means to enter them easily, I'll have I think all that I need.
Events
An event is something that occurs at a time and generally has a start-time, end-time and duration. Having any two allows you to calculate the third automatically. So we put an "Event" object into our software and put them to use because I have events from the ResMed S9 AutoSet; hypopneas, obstructive apneas, central apneas and recording start events. In ResMed terms, the apneas have an end-time and duration because they are determined after the fact, and the recording start event is instantaneous: the start-time only. These are already gathered and stored in our real-time historian with the ResMed data collection we do. This is spiffy because our software has multiple tasks, an spO2 and ResMed file watcher watching a directory and when I've gathered the files I just drag and drop them into that folder where they are "sucked up" and the data is put into the real-time database and the original files are automatically archived for back-up purposes. OK, I'm getting off topic...
I need to add my own events too, such as periods of time I feel groggy, or really good, or something else of merit that should be recorded.
Doses
A close cousin to an event is what I call a "Dose". This is an event like activity (has a time and maybe a duration) that has a quantity associated with it. I call it a Dose because it's like taking a medicine. "I took X mg of Y drug at Z time", or I just drank a full pot of coffee at this time. Even exercise is like a dose, "I averaged an aerobic heart rate of X from this time to that time". Having these events, time stamped, with quantities, gives me information about how much, how long before sleep-onset they occurred, or totaled during the day. This way I can log that I had a pound of steak for dinner, or took two Excedrin at 10 PM or had an hour of "this strenuous" exercise at 2 PM or 1 cup of Tulsi Tea 10 minutes before bed, etc.
Once I have these Events and Doses, and a means to enter them easily, I'll have I think all that I need.
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.
Friday, January 27, 2012
Now have Zeo, CMS and ResMed Data Together
OK, we finally have a successful mechanism to import, store, extract and synchronize Zeo brainwaves and sleep stage classifications (gathered real-time), CMS50E heart rate and spO2 (gathered post-sleep) and now data from the ResMed S9 AutosSet (post-sleep also). The CMS50E data we, in theory, could capture in real-time as well, but we will leave it a post-sleep import for now. If we need to do something with it in real-time we'll do it.
Here's an example chart of such synchronized data:
So, in our database we have:
CMS50E:
spO2, Pulse
Zeo (real time)
Delta, Theta, Alpha, Beta 1, Beta 2, Beta 3, Gamma, Sleep Stage,
ResMed:
Mask Pres, Therapy Pres, Exp Press, Leak, RR, Vt, MV, Snore Index, FFL Index, Flow_HD, Mask Pres_HD
Next, I'll come up with a way to summarize various measures from these time series on a nightly basis, as I think I want to analyze and optimize on a nightly basis... what happened the day(s) before, what happened during the night and how will I feel the next day.
As a part of this, I will also create my own "Sleep Stage" metrics, probably not following the medical standards, but something more meaningful. Sleep is not "binary mutually exclusive states" (Wake, Light, Deep, REM) but as can be seen in the brainwaves, a continuous shifting between various forms of sleep.
Here's an example chart of such synchronized data:
So, in our database we have:
CMS50E:
spO2, Pulse
Zeo (real time)
Delta, Theta, Alpha, Beta 1, Beta 2, Beta 3, Gamma, Sleep Stage,
ResMed:
Mask Pres, Therapy Pres, Exp Press, Leak, RR, Vt, MV, Snore Index, FFL Index, Flow_HD, Mask Pres_HD
Next, I'll come up with a way to summarize various measures from these time series on a nightly basis, as I think I want to analyze and optimize on a nightly basis... what happened the day(s) before, what happened during the night and how will I feel the next day.
As a part of this, I will also create my own "Sleep Stage" metrics, probably not following the medical standards, but something more meaningful. Sleep is not "binary mutually exclusive states" (Wake, Light, Deep, REM) but as can be seen in the brainwaves, a continuous shifting between various forms of sleep.
Friday, January 20, 2012
Equipment
I have a variety of equipment that I am using and I might get more, we'll see. Here's my list:
- ResMed S9 AutoSet. This is a medical device that is a fully data capable auto positive airway pressure (APAP) sleep apnea treatment system. It applies a varying air pressure to my face using a sealed mask, which forces my airway open if it needs to as I sleep. This device gives me information such as:
* Event Flags: What kind of breathing event I have, when it occurred and for how long
* Air Flow Rate as I breath in and out
* Mask Pressure which varies as the machine tries to eliminate events
* Tidal Volume which is the amount of air I'm breathing in and out
* Minute Ventilation, similar to Tidal Volume, but the amount per minute.
* AHI, an index that reports the events/hour.
* Leak rate (how much the mask is leaking)
* Snore Index (how much I'm snoring)
* Respiration Rate (breaths / minute)
Data from the ResMed S9 AutoSet is from an SD card, which you pop out of the ResMed S9 AutoSet and put into a card reader in your PC. Presently, until I can get this data into our software, I use SleepyHead to view trend charts with it.
Note: I highlight the word AutoSet because so there is no confusion with other ResMed "Auto" machines that are not necessarily data capable.
. - CMS 50 E Pulse Oximeter. This is a that device clips on my finger and as I sleep it records my heart rate and blood oxygen levels (spO2). It is not a medical device, and is therefore not very accurate, but good enough to know what is going on. The pulse rate is reasonably accurate. The spO2 is within 2% when above a 70% spO2 reading.
Data from the CMS 50 is available through a provided USB/Serial cable and the data can stream from the device in real-time, or the device can store it for up to 24 hours each session and then it can be transferred to your PC using the provided USB/Serial cable. It comes with two software applications; real-time and session review (SpO2 Review). I use the latter to fetch sessions off of the device and the SpO2 Review application dumps the data to disk, which then I import into our software.
Available from Amazon (?) or the PulseOxStore.
Software and the device driver, if you need them, may be found here at the PulseOxStore.
. - Zeo Bedside Sleep Management System. (psst... you can get it cheaper on Amazon). A rather cool non-medical device that has a headband that you wear and it measures electrical activity through the skin on your forehead. This activity is in part facial movements but principally your brain's frontal lobe electrical activity. The Zeo Bedside gathers this data in a fancy alarm-clock and generates various information about your sleep, most notably crude, but generally correct, estimates of what your sleep stages (Wake, REM, Light and Deep) were during the night every 5 minutes. It is computing this every 30 seconds based on frequencies calculated every second, based on a brain electrical activity measured 128 times per second.
Data from the Zeo is available either through
* An SD card, on which there is a night's sleep session, which then can be transferred to your PC, uploaded to their web site and used in a user friendly sleep coaching system with lots of interesting charts, statistics and such. You can also download data, summarized by night, to your PC again in a CSV file, one column of which has 30 second sleep stage estimates.
* A serial port in real time. The Zeo does not come with a USB/Serial cable however, you must make one. :( I did and I'll tell you how. And when you do make one, there is an application called ZeoScope that enables you to see your brainwave and the amplitude (I think) of Alpha, Beta (1, 2, 3), Delta, Gamma, Theta frequencies the impedance of the band on your skin and also the sleep stages the Zeo is estimating.
Presently, I use both the SD card / web site to get Sleep Stage charts and a serial cable to collect the real-time stream into our software. - X16-1C Accelerometer by Gulf Coast Data Concepts. Tells me the orientation of my body and head while I sleep, such as on my belly, head to left or right, or on my back, head left or right. This device confirmed without a doubt my positional sleep apnea.
This device is not only an accelerometer, but a USB thumb drive that contains the data it creates in text CSV file format. Spiffy ! Easy.
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