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When we put this technology into the consumer’s hands for the first time, we said “We have
a great way to wake you up feeling better”. Some of them came back to us and said “Yes!
Absolutely you do; this is great!” and most of them came back and said, “Wait, what’s
this Deep Sleep thing?” “What’s this REM Sleep thing?” “What does all this
data mean?” “One: Am I normal?” and “Two: Can I do anything about it if I’m
not?”?
And then you start getting those people who say “Well, if I am normal, how can I get
super normal?”
So we started learning from this experience that people are really curious about sleep
and we have the opportunity for the first time to open up what’s actually happening
on a night-to-night basis, so we’ve taking the platform a lot farther than just we want
to wake you up because honestly, that’s a feature that’s great for a select group
of people but there’s a lot more power to give people information about the third of
their lives they can’t know about otherwise.
We’re limited to the amount that we can fit on the forehead and if I had a sensor
pad you can see it cover up a good majority of the forehead. You can slide it back and
forth a bit, up and down a little bit, but we haven’t found a huge difference in terms
of accuracy when you do that.
I do have one night that I recorded about a year and a half ago where I had shaved my
head for Halloween and wore three Zeos at once: one [on the forehead, one on the top
and one at the back]. The one [on the forehead] worked a lot better; this one [at the top]
did okay; this one [the back] didn’t do too well and I’m guessing that it had to
do with all that alpha activity that’s generated in the back of the brain that our neural network
doesn’t know anything about.
Q: So it’s a matter of interpreting the signal rather than where the sensor is placed?
A: Yes, absolutely.
Q: So do you get a lot of artifacts moving around?
A: We get plenty of artifacts but it’s another one of those places where I’m really impressed
with the neural network that’s able to work itself through a lot of that artifact. The
picture that I showed of the raw data is filtered very heavily even from the raw signals that
the neural network can see. So it’s pretty robust in terms of GSR and all that.
It varies quiet a bit. The one thing I can tell you for sure is if you wake up out of
Deep sleep, you are obliterated.
That’s the experience of when you wake up and you feel like you can’t think, you don’t
want to move, you’d rather just go back to sleep. That’s usually what would happen
if you came out of that Deep sleep, that heavy sleep inertia. That’s what we mean when
we say “sleep inertia”: it’s that period of time when you’re groggy.
You wake up out of Deep sleep and it could be hours before you’re functioning at a
normal level. Waking up out of a transition is usually the best place so like Light--REM
sleep or vice-versa is considered to be an optimal way of reaching peak performance pretty
quickly.
ZQ is a summary measure that we use. It’s made up of Total Sleep Time and it’s about
70-75% how much total sleep you got; and you get some bonus points for getting REM Sleep,
Deep Sleep, and we take some points away for the amount that you’re awake during the
night. So if you wake up a lot and you’re awake for big chunks we’re going to pull
some points out.
The idea there is to give you a chance when you wake up in the morning to see a single
number that isn’t solely dependent upon “I went to bed at this time and I got up
at this time.” It’s really consumer oriented; this is not a scientifically-validated measure
for sleep quality but it is a way for you to see “I got an 80 last night; that’s
good for me; I’m going to be good for today” or “I got a 40 last night and I’m going
to be freaking miserable unless I take a nap at some point today.”
We have a full open Zeo platform so we have a Web API and we have a couple of libraries
for increased access. We have a raw data library so you can get that 128Hz information out
of the serial port out of the back of the base station.
Speaker: That answers all my questions.
So the SD card actually has encrypted data on it normally. We have an open initiative
to have that de-crypted so that you can work on your desktop.
There are large variations in the amount of REM Sleep, Light Sleep, and Deep Sleep; two
major factors that influence that are age and gender. As you get older, you get less
Deep sleep and women tend to get more Deep sleep and, in our database we’re finding,
slightly less REM sleep.
The Deep sleep thing, I’ll just cover right now: as you’re getting older, it could be
less brain mass and/or a decrease in activity from those neurons firing at the same time
but if you look at the rules based on scoring Deep sleep it’s actually based on amplitude.
But that doesn’t mean that older people are not getting slow waves; it just means
that they’re not getting as big. So unclear as to whether or not it’s truly meaningful.
As to the difference between men and women on Deep sleep, women have thinner skulls so
it might look like they’re getting more Deep sleep because the signal is getting through
the skull easier so it looks like it’s higher amplitude.
REM sleep--huge differences and there are many factors that can play into that which
are incredibly meaningful. One of the biggest ones, depression, is linked with an over-active
REM state, so people with excessive REM--and I’m talking a lot of REM--tend to have anxiety
or depression issues that can be solved through medication.