What is the main focus of the video?

The video focuses on testing the heart rate and sleep tracking capabilities of the Xiaomi Mi Band 10.

Who is the presenter of the video?

The presenter is Rob, a post-doctoral scientist specializing in biological data analysis.

How did the Mi Band 10 perform in heart rate tracking?

The Mi Band 10 showed promising results in heart rate tracking with a correlation of 0.99 compared to a Polar H10 chest strap.

What were the results for sleep tracking?

The sleep tracking results were inconsistent between the two Mi Band 10s, with one performing better than the other.

Is the Mi Band 10 a good option for heart rate tracking?

Yes, for its price point, the Mi Band 10 performs well in heart rate tracking.

What are the limitations of the Mi Band 10?

The Mi Band 10 lacks reliability in sleep stage tracking.

What other devices were mentioned in the video?

Other devices mentioned include the Polar H10 chest strap, Whoop Strap, and Huawei Watchfit.

What is the price range of the Mi Band 10?

The Mi Band 10 is priced around 40 to 50 dollars.

What does Rob plan to do next with the Mi Band 10?

Rob plans to conduct more tests and possibly have others test the device for consistency.

What is the overall conclusion about the Mi Band 10?

The Mi Band 10 is a good option for heart rate tracking but not reliable for sleep stage tracking.

Mi Band 10 - Scientific Review (AMAZING!)

00:38:21

https://www.youtube.com/watch?v=qnriFKto38U

Zusammenfassung

TLDRIn this video, Rob, a post-doctoral scientist, tests the Xiaomi Mi Band 10 for heart rate and sleep tracking. He unboxes two bands, connects them to different phones, and conducts initial tests including fake workouts and real exercises like indoor cycling and weightlifting. The heart rate tracking shows promising results with a correlation of 0.99 compared to a Polar H10 chest strap. However, sleep tracking results are inconsistent between the two bands, with one performing better than the other. Overall, the Mi Band 10 performs well for heart rate tracking but lacks reliability in sleep stage tracking.

Mitbringsel

📦 Unboxing two Mi Band 10s for testing.
📱 Connecting to different phones and accounts.
💪 Initial tests include fake workouts and real exercises.
📊 Heart rate tracking shows a correlation of 0.99 with Polar H10.
😴 Sleep tracking results are inconsistent between the two bands.
💰 Mi Band 10 is priced around 40-50 dollars.
👍 Good option for heart rate tracking.
❌ Not reliable for sleep stage tracking.
🔄 More tests planned for consistency.
📈 Overall, promising results for a budget device.

Zeitleiste

00:00:00 - 00:05:00
Rob introduces the video, explaining that he will test the heart rate and sleep tracking capabilities of the Xiaomi Mi Band 10. He mentions his background as a post-doctoral scientist and outlines the plan to unbox and set up the devices for testing.
00:05:00 - 00:10:00
After unboxing the Mi Bands, Rob connects them to two different iPhones and Xiaomi accounts. He discusses previous syncing issues with Xiaomi devices and hopes to successfully sync the heart rate data to the Strava app for analysis.
00:10:00 - 00:15:00
Rob performs a quick indoor cycling workout to test the heart rate tracking of both Mi Bands. He notes the initial heart rate readings and mentions the need to reconnect the devices to Strava for data syncing.
00:15:00 - 00:20:00
Following the indoor cycling session, Rob analyzes the heart rate data from both Mi Bands compared to a Polar H10 chest strap. He finds a high correlation of 0.99, indicating that the Mi Bands performed well in tracking heart rate during the workout.
00:20:00 - 00:25:00
Rob transitions to weightlifting, noting that tracking heart rate during this activity is more challenging. He compares the heart rate data from both Mi Bands and finds that while they performed decently, they struggled to accurately capture peak heart rates during intense lifts.
00:25:00 - 00:30:00
Rob then tests the Mi Bands during outdoor cycling, analyzing the heart rate data from two rides. He finds that the Mi Bands performed well, with correlation values of 0.91 and 0.96, indicating good tracking accuracy compared to reference devices.
00:30:00 - 00:38:21
Finally, Rob discusses the sleep tracking performance of the Mi Bands, revealing discrepancies between the two devices. He compares their sleep stage data to an EEG device and concludes that the Mi Bands did not perform well in this aspect, particularly in tracking REM and light sleep stages. He summarizes the overall findings, highlighting the Mi Band 10's strong heart rate tracking but poor sleep tracking capabilities.

Mind Map

Video-Fragen und Antworten

What is the main focus of the video?
The video focuses on testing the heart rate and sleep tracking capabilities of the Xiaomi Mi Band 10.
Who is the presenter of the video?
The presenter is Rob, a post-doctoral scientist specializing in biological data analysis.
How did the Mi Band 10 perform in heart rate tracking?
The Mi Band 10 showed promising results in heart rate tracking with a correlation of 0.99 compared to a Polar H10 chest strap.
What were the results for sleep tracking?
The sleep tracking results were inconsistent between the two Mi Band 10s, with one performing better than the other.
Is the Mi Band 10 a good option for heart rate tracking?
Yes, for its price point, the Mi Band 10 performs well in heart rate tracking.
What are the limitations of the Mi Band 10?
The Mi Band 10 lacks reliability in sleep stage tracking.
What other devices were mentioned in the video?
Other devices mentioned include the Polar H10 chest strap, Whoop Strap, and Huawei Watchfit.
What is the price range of the Mi Band 10?
The Mi Band 10 is priced around 40 to 50 dollars.
What does Rob plan to do next with the Mi Band 10?
Rob plans to conduct more tests and possibly have others test the device for consistency.
What is the overall conclusion about the Mi Band 10?
The Mi Band 10 is a good option for heart rate tracking but not reliable for sleep stage tracking.

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Untertitel

Automatisches Blättern:

00:00:00
I just ordered and received two Mi Band
00:00:02
10 and today we're going to
00:00:04
systematically and scientifically test
00:00:06
them to find out how good the heart rate
00:00:08
tracking and the sleep state tracking is
00:00:10
of these cheap Xiaomi watches. By the
00:00:12
way, for those of you who don't know me,
00:00:14
my name is Rob and I'm a post-doal
00:00:15
scientist specializing in biological
00:00:17
data analysis. Now, this video is going
00:00:19
to be a bit different from my normal
00:00:20
ones in two ways. First of all, this is
00:00:23
going to be an initial test, just a few
00:00:25
exercises, one or two nights of sleep
00:00:27
maximum, just to get an initial
00:00:28
impression of how well these watches can
00:00:30
track your heart rate and your sleep.
00:00:32
And second, we're going to together go
00:00:34
on the journey to install these watches,
00:00:36
see if we can actually get to the data,
00:00:38
because that's one problem with Xiaomi
00:00:40
devices. Often, it's very hard to
00:00:42
actually get to the raw data and do the
00:00:44
analysis I like to do. So maybe we'll
00:00:46
have a lot of trouble and you'll have
00:00:48
the same frustrations as me, but you'll
00:00:50
also be informed that it's hard to
00:00:51
actually sometimes get to this data. Now
00:00:53
to get started, we need to unbox them
00:00:54
and connect them to two different phones
00:00:56
and two different Xiaomi accounts. So
00:00:58
let's do that. So I have two iPhones
00:01:00
here, both with a separate Mi Fitness
00:01:03
account, both syncing to both Apple
00:01:05
Health, also two separate Straa
00:01:07
accounts. So there I should be able to
00:01:09
get the heart rate data. And this has
00:01:11
been an issue in the past. Sometimes for
00:01:13
some reason it just doesn't sync. So
00:01:15
before I actually tested both the Xiaomi
00:01:17
Watch and the Xiaomi Smart Band 9 Pro
00:01:20
and only for the Band 9 Pro did I
00:01:22
actually get the heart rate data on
00:01:23
Straa and for some reason it just didn't
00:01:26
sync at all for the Xiaomi Watch. So I'm
00:01:28
actually reusing the account I had for
00:01:30
the Band 9 Pro and I created a new
00:01:32
account on a new phone for one of the
00:01:34
other bands. So both should hopefully
00:01:36
now sync to Straa. Let's first quickly
00:01:39
unbox both devices. So I actually
00:01:41
ordered two different colors so we can
00:01:43
tell them apart. a white one and a black
00:01:46
one. Well, the boxes are simple as
00:01:49
always. We have the band and the charger
00:01:52
right here. Still using the old USBA. It
00:01:55
is what it is. And then we also have our
00:01:59
black one right here. Same setup again.
00:02:03
USB typeA
00:02:05
and the black version.
00:02:11
So, let's first set up the black one. As
00:02:14
always, the bezel is pretty good. So,
00:02:16
let's set up the black one on my gold
00:02:19
iPhone.
00:02:22
So, that was easy enough. A quick update
00:02:25
and then at the same time, we can
00:02:27
install the other one. Here we have the
00:02:31
white version. So, here you can see
00:02:33
previously I had the Xiaomi Band 8 9 Pro
00:02:36
and another 9 Pro connected, but we're
00:02:39
actually going to connect a new device.
00:02:44
All right, so both devices are now
00:02:47
updating. Let's wait for that to be done
00:02:50
and then we're going to do a test
00:02:51
exercise. Just a 5 minute fake exercise
00:02:54
to see if the data will sync to Straa.
00:02:56
And if that works, it's time to get to
00:02:57
the real testing. But now, as always,
00:02:59
since I have to wait for those updates
00:03:01
to get done, I can make myself a quick
00:03:04
coffee and we can enjoy that while we're
00:03:06
waiting.
00:03:08
[Music]
00:03:21
Okay, so the update is done. The coffee
00:03:24
is ready.
00:03:27
And now I'll start two fake workouts
00:03:28
just to see if that data syncs. So let's
00:03:30
do that now. That also means I cannot
00:03:32
test the Vivo Active 6 from Garmin for
00:03:34
at least today and tomorrow. And I'm
00:03:36
actually also testing another device you
00:03:38
guys are very interested in, the
00:03:40
Amazefitit Helios band. So we have the
00:03:43
strap of it right here. So this is the
00:03:45
strap part, but I'm actually going to be
00:03:47
able to wear it at the same time because
00:03:49
I hacked that together by using the
00:03:51
Whoop Strap 4.0 biceps. I don't know
00:03:54
what you call these things. like a bicep
00:03:56
sleeve or something. So, I'll be wearing
00:03:58
that as well for the coming weeks in
00:04:00
addition to a second Helios band I'll be
00:04:02
wearing on my wrist and then we'll also
00:04:03
do that review in a week or two. I'm
00:04:05
very excited about this one. This could
00:04:07
be a whoop replacement without a
00:04:09
subscription. So, wait for that as well.
00:04:10
If you're interested, subscribe to the
00:04:12
channel. But for now, of course, the
00:04:14
next two days we're going to focus on
00:04:15
the Xiaomi Mi Band 10. Let's first try
00:04:17
an indoor workout because sometimes
00:04:20
those don't sync to Straa. There's some
00:04:21
weird things going on. Again, you have
00:04:24
to wear the device a bit away from the
00:04:26
wrist. So, that should be okay. So,
00:04:28
we'll go.
00:04:30
And also for the second device, same
00:04:33
information. Let's go. Okay. So, we'll
00:04:37
wait 5 minutes or so. You can see the
00:04:40
heart rate is not even being detected
00:04:42
yet. I don't know if you can see that
00:04:43
screen right now. So, as you can see,
00:04:46
it's not detecting my heart rate yet,
00:04:48
which is weird. Let's see if my heart
00:04:50
rate will pop up. Yes. 76 73 which is
00:04:53
reasonable I would say. And for the
00:04:56
other Mi Band, will the heart rate pop
00:04:58
up? 96. That's probably a bit too high.
00:05:02
5 minutes later. Okay, so we're 5
00:05:04
minutes in the moment of truth. Let's
00:05:08
stop both the watches. So, the black one
00:05:13
and the white one. Okay, one
00:05:17
worked. The other one worked as well.
00:05:20
Where is strong? Here we go. Activities.
00:05:25
No, no Sava drink. No, no Straa sync.
00:05:30
Let's try again. So, we did a freestyle
00:05:32
workout. It recorded my heart rate with
00:05:35
the Xiaomi Ben 10, but it's not on
00:05:37
Straa. Let's reconnect, maybe.
00:05:42
[Music]
00:05:45
And we'll be back in another 5 minutes.
00:05:47
One long angry line later. All right,
00:05:50
we're back. Five minutes later. Let's
00:05:52
end the exercise. Whoopsie. Let's check
00:05:56
Straa. Yes.
00:05:59
Okay, apparently I needed to reconnect
00:06:01
or maybe for some reason was connected
00:06:03
to a different account. All seems to
00:06:06
work now. Okay, that's good. All seems
00:06:08
to work now. So, my plan is to first do
00:06:11
maybe an indoor cycling session, then a
00:06:14
short weightlifting session, probably
00:06:16
chest and triceps. Then I actually have
00:06:18
a party to go to, but I'll cycle there.
00:06:20
So, we'll get some cycling data back and
00:06:22
forth. And then, yeah, that's it. Maybe
00:06:24
tomorrow I'll go for a run and then we
00:06:26
have a bunch of data to look at. Of
00:06:28
course, it's a very initial test, but it
00:06:29
will show us for two independent Xiaomi
00:06:32
Mi Band 10s if they're good at tracking
00:06:33
my heart rate. So, let's get started.
00:06:35
So, we'll start with indoor cycling
00:06:38
right here, which should be relatively
00:06:40
easy for a device to track. So, let's
00:06:42
see if the Xiaomi Mi Band 10 can track
00:06:44
my heart rate during indoor cycling.
00:06:47
[Music]
00:06:54
Okay, that was quite an intense workout.
00:06:56
Just looking at my wrist a few times,
00:06:58
checking the Mi Band 10's heart rate,
00:07:00
and I compared that to the chest strap
00:07:02
by Garmin. Actually, that looked very
00:07:03
similar. So, that looks good at a first
00:07:05
glance, but we're actually going to do
00:07:06
formal analysis and do some coding on my
00:07:08
computer. Now, just one thing I want to
00:07:10
mention, for some reason, Garmin always
00:07:12
gives me a way too high V2 max. So, it
00:07:15
says I have a V2 max of 68, which is way
00:07:18
below what I actually have. I have a V2
00:07:19
max of 58 according to my last
00:07:21
measurement, but that's a side note.
00:07:23
Usually, the Garmin can measure my heart
00:07:24
rate quite accurately, but we're going
00:07:26
to use the Polar H10 as a reference in
00:07:28
this case. But from what I've seen,
00:07:30
basically, whatever chest strap you get,
00:07:31
you get a good heart rate. So, use the
00:07:33
chest strap by Polar as a reference and
00:07:35
see how good the Mi Band 10 actually
00:07:36
did. Okay, the results are in for indoor
00:07:39
cycling and the results are looking
00:07:41
surprisingly good. Now in this plot you
00:07:44
see the overview for the Mi Band 10 worn
00:07:46
on my left wrist with along the
00:07:48
horizontal axis the reference device. So
00:07:50
the Polar H10 chest strap and along the
00:07:52
vertical axis the Mi Band 10 where each
00:07:54
dot is a matching measurement between
00:07:56
the two of them. And if they would
00:07:58
perfectly agree all values should be
00:08:00
along this blue line right here. And as
00:08:02
you can see almost all points are on or
00:08:05
at least super close to the blue line.
00:08:07
And for such a cheap device as the Mi
00:08:09
Band this is really good. We can
00:08:12
actually quantify this agreement with a
00:08:14
correlation, this R value up here, which
00:08:16
is 0.99 for the one on my left wrist.
00:08:19
So, super good. I'm really happy with
00:08:21
this. And we can look at this same thing
00:08:22
for the device on my right wrist. And
00:08:24
those results are right here. Now,
00:08:26
they're not identical. There's this
00:08:28
little bit of deviation right here, but
00:08:31
overall, again, a correlation of 0.99,
00:08:34
which is really good, and almost all
00:08:36
points on or close to the blue line.
00:08:39
Now, let's take a look at the individual
00:08:40
sessions to see why there's still a bit
00:08:42
of deviations, but this result really
00:08:44
surprises me so far. Along the
00:08:46
horizontal axis, we have the clock time
00:08:47
and my heart rate along the vertical
00:08:49
axis with in blue green the reference
00:08:51
device and the Mi Band 10 from my left
00:08:53
wrist in red and the red line and the
00:08:55
blue line basically overlap perfectly.
00:08:58
Like there's a little bit of deviation
00:08:59
here in the beginning and maybe
00:09:01
sometimes in the lower heart rate range,
00:09:03
a tiny bit of deviation, but overall
00:09:06
definitely good enough performance. And
00:09:08
if we look at the one on my right wrist,
00:09:10
this is more or less the same. So a very
00:09:12
good agreement. Only in this moment
00:09:15
right here, they detect a slightly too
00:09:17
high heart rate, but just for a little
00:09:18
bit. Overall, this is really good and
00:09:21
good enough for me. And we can actually
00:09:22
put these results into the context of
00:09:24
many of the other devices I've tested
00:09:25
before. And those results are displayed
00:09:27
right here. So that correlation value
00:09:29
we're looking at before is along the
00:09:30
horizontal axis. And on the vertical
00:09:33
axis, I ordered the watches from worst
00:09:35
on the bottom to best on top. So the
00:09:37
further to the right and the higher
00:09:39
devices, the better is its agreement
00:09:40
with the reference device. And here I
00:09:42
marked the Mi Band 10 on my left wrist
00:09:44
in red. And we'll zoom in a bit in a
00:09:46
moment so you can also see where the one
00:09:47
on my right wrist is. And here we have
00:09:49
that zoomed in view. So these are just
00:09:50
the devices with a correlation of 0.9 or
00:09:53
higher. So some of the better devices
00:09:55
with again the one on my left wrist
00:09:57
marked in red right here and the one on
00:09:59
my right wrist right here. So they're
00:10:01
super close to each other and among some
00:10:03
of the better devices out there. They're
00:10:05
really doing well. Now, this is a very
00:10:07
limited initial test, so just a single
00:10:09
spinning session, but the fact that both
00:10:11
of them performed really well is at
00:10:12
least promising. So, overall, I'm quite
00:10:15
surprised and really happy with this.
00:10:17
Let's see if we can see some of the
00:10:18
other Mi Bands in this overview. So, we
00:10:20
have the Mi Band 8 right here. So, quite
00:10:22
a bit worse. Again, I will probably have
00:10:25
done more testing with that one. And the
00:10:27
Mi Band 9 is in this overview. And
00:10:30
indeed, the Mi Band 9 also didn't do
00:10:31
that poorly. It's right here. is also
00:10:34
quite close to the Mi Band 10. So, I
00:10:36
would say the Mi Band 10 might be doing
00:10:37
a tiny bit better than the Mi Band 9,
00:10:39
but overall really good performance. But
00:10:42
let's next take a look at a much harder
00:10:44
exercise for this device to track
00:10:46
weightlifting. Well, for any device to
00:10:48
track. So, with weightlifting, there's a
00:10:49
lot of tension on your arms. And this
00:10:51
makes it very hard for any tracker out
00:10:53
there to accurately track your heart
00:10:55
rate on the wrist. So, let's do that
00:10:56
now. Afterwards, we'll take a look at
00:10:58
cycling outside. I actually need to fix
00:10:59
one of my bikes back there. We'll fix
00:11:01
that and then go for cycling. But let's
00:11:03
first do a weightlifting session. And
00:11:05
here we have a similar overview to
00:11:06
before, but now for weightlifting with
00:11:08
again the reference device along the
00:11:10
horizontal axis and the Mi Band 10 on my
00:11:13
left wrist along the vertical axis. And
00:11:15
we do see a typical pattern I would say.
00:11:18
So in the lower heart rate range almost
00:11:20
all points are on or at least super
00:11:22
close to the blue line. So there the
00:11:24
measurements are okay. But here in the
00:11:26
higher heart rate range, there are many
00:11:28
points below the blue line, indicating
00:11:30
that in these moments, the Mi Band 10
00:11:31
detected a too low heart rate. Now, this
00:11:33
generally means that when I have a peak
00:11:35
in my heart rate, so there's a lot of
00:11:37
tension on my arm, the Mi Band 10 cannot
00:11:39
detect my heart rate accurately. But
00:11:40
let's now take a look at the one on my
00:11:42
right wrist. And here we have those
00:11:44
results. And these are mostly the same,
00:11:46
though even a little bit better. There
00:11:47
are more points in the higher heart rate
00:11:49
range close to the blue line, but we
00:11:51
still see many points below the blue
00:11:53
line right here. The correlation value,
00:11:55
that value you're looking at before is
00:11:56
now 0.92 for the one on my right wrist
00:12:00
and 0.89 for the one on my left wrist.
00:12:02
And this is actually quite decent
00:12:04
compared to the competition. But let's
00:12:06
first take a look at the individual
00:12:07
session and then we'll compare to the
00:12:09
competition. And here are the results
00:12:10
for the Mi Band 10 on my left wrist with
00:12:13
again the Mi Band 10 in red and the
00:12:14
reference device in blue green. Now,
00:12:16
each time I did a set of exercise, my
00:12:18
heart rate showed a peak and you can see
00:12:20
that clearly by these blue lines right
00:12:22
here. And it is pretty obvious that the
00:12:24
Mi Band 10 often couldn't fully detect
00:12:26
the peaks in my heart rate, at least for
00:12:28
the one on my left wrist. And if we look
00:12:29
at the results for the one on my right
00:12:31
wrist, these are potentially a bit
00:12:32
better. Some of the peaks were detected.
00:12:35
I would say these two, so this one right
00:12:36
here, this one right here, and also this
00:12:38
first one actually were more or less
00:12:40
fully detected, but many peaks were also
00:12:43
missed. So I wouldn't say this is good
00:12:44
enough. But compared to the competition,
00:12:47
this actually isn't that bad. So let's
00:12:49
take a look at that. And here we have
00:12:50
those results. So a similar overview to
00:12:52
before where we want the devices to be
00:12:54
as far to the top right as possible with
00:12:56
the Mi Band 10 on my right is marked in
00:12:59
red right here with that correlation of
00:13:01
0.92. It's actually pretty decent among
00:13:03
some of the better devices out there.
00:13:05
And if we zoom in a bit, we can read
00:13:07
those labels even better. These are all
00:13:09
devices with a correlation of 0.7 or
00:13:11
higher. And here we have the Mi Band 10
00:13:13
on my right wrist. And a little bit
00:13:15
below that right here is the Mi Band 10
00:13:17
on my left wrist. And they're super
00:13:19
close actually. So more or less giving a
00:13:21
similar result. I do see some difference
00:13:23
sometimes in performance for devices on
00:13:25
my left and right wrist where actually
00:13:27
in general my left wrist seems to be a
00:13:29
bit easier. For the Mi Band I cannot see
00:13:31
any difference so far. And with this
00:13:33
correlation it is among some of the
00:13:34
better devices out there. Maybe doing
00:13:37
about as well as many Huawei devices.
00:13:39
Not quite as good as Apple watches.
00:13:41
These are some of the best devices out
00:13:43
there for heart rate tracking. But for
00:13:45
the price, this is honestly really good.
00:13:47
I'm not disappointed with this. Now, for
00:13:49
weightlifting, I still wouldn't use it.
00:13:51
I generally wouldn't use any device on
00:13:53
the wrist except for maybe the Apple
00:13:55
Watch. But if you want to track your
00:13:56
heart rate during weightlifting, I
00:13:57
really recommend using a chest strap.
00:13:59
But let's next take a look at cycling.
00:14:01
That will be the most important test to
00:14:03
do because that's quite a bit harder
00:14:05
than cycling indoors and also quite
00:14:07
important for many people, but not quite
00:14:09
as hard as weightlifting. But before
00:14:11
doing that, I actually need to fix one
00:14:12
of my bikes. So, I have a bunch of bikes
00:14:14
right here. Actually, have a few more
00:14:16
bikes. I actually need to fix the
00:14:18
tension on the spokes of the back wheel
00:14:20
right here. I already partially fixed it
00:14:22
before, but there's still a small issue.
00:14:24
I need to replace the pedals right
00:14:26
there. And then hopefully it'll be ready
00:14:28
to ride. I actually used that bike for
00:14:29
many years for my road biking. My
00:14:32
friends had all these fancy bikes and I
00:14:33
was still on my old steel bike with
00:14:35
frame shifters. It still worked. It was
00:14:38
a bit of a challenge keeping up with
00:14:39
them, but good for my fitness. I now
00:14:41
have a somewhat newer bike, still from
00:14:43
the 2000s, I think. Let me quickly show
00:14:45
you that one. This is actually my
00:14:46
current road bike right here. It's from
00:14:48
the early 2000s. I think back then it
00:14:51
was an amazing bike, but it's still
00:14:53
mostly aluminium. So, if there are any
00:14:55
bike brands out there who want to
00:14:56
sponsor me, I'm a really keen cyclist. I
00:14:59
cycle a lot, but on quite old bikes and
00:15:01
I'm happy to try out some carbon bikes
00:15:03
sometimes. Decathlon for instance, I
00:15:05
send you a message. I love your VR rial
00:15:07
stuff. I have a lot of your kit. So, if
00:15:09
you ever want to have me try one of your
00:15:10
bikes, I'd love to. But I'd be happy
00:15:12
with any brand that produces quality
00:15:14
carbon frames.
00:15:16
[Music]
00:15:20
All right, I'm back from my bike rides.
00:15:22
I already analyzed the data and it's
00:15:24
super interesting. There were just two
00:15:26
short bike rides, both about 30 35
00:15:28
minutes or so, but the data is pretty
00:15:30
clear, I would say. And with two
00:15:32
watches, we basically have four rides to
00:15:34
look at. So, let's take a look. And
00:15:36
sorry I'm not wearing a shirt in some of
00:15:37
this video, but it's about 27° C now in
00:15:41
my room. Way too hot for me. I don't
00:15:43
know what it is in Fahrenheit. Alex can
00:15:44
put it here. But let's take a look at
00:15:46
the data now. Instead of jumping
00:15:47
straight to the correlations, I first
00:15:49
want to take a look at the bike rides
00:15:51
themselves. This is the first ride right
00:15:53
here with the reference in blue green
00:15:55
and the Mi Band 10 worn on my right
00:15:57
wrist in red. And this looks really
00:15:59
good. Honestly, the Mi Band 10 mostly
00:16:02
was able to follow along with the
00:16:03
changes in my heart rate. Yes, some of
00:16:05
the details are missing, but overall
00:16:08
looking pretty good. This would be good
00:16:10
enough for me. And let's now take a look
00:16:11
at this same ride, but now for the one
00:16:13
on my left wrist. And those results are
00:16:16
right here. Also looking pretty good. It
00:16:18
makes some different mistakes, but
00:16:20
overall more or less the same
00:16:22
performance, I would say. And the second
00:16:24
bike ride actually looks a lot worse for
00:16:26
the one on my right wrist. Still not as
00:16:28
bad as we've seen for some devices. We
00:16:31
see quite some deviation especially here
00:16:33
in the first half of the ride. We can
00:16:35
see that the red line is sometimes too
00:16:37
high like right here for instance or
00:16:39
right here and sometimes too low like
00:16:41
right here. But the one I wore on my
00:16:44
left wrist actually did a bit better for
00:16:46
this ride. This is much closer to
00:16:48
reality. So this again would be good
00:16:50
enough for me. Let's now take a look at
00:16:52
those correlations. And let's start with
00:16:54
the Mi Band 10 on my right wrist because
00:16:56
that showed worst performance for the
00:16:58
second ride. And here we have an
00:17:00
overview of those results which still
00:17:02
have a pretty decent correlation at 0.91
00:17:05
which is much better than many devices
00:17:07
out there. And generally most points are
00:17:10
close to the blue line. Though as we can
00:17:11
see here in the lower heart rate range
00:17:14
sometimes detected too high heart rate
00:17:16
and in the higher heart rate range it's
00:17:18
sometimes detected at too low heart
00:17:20
rate. And this is related to what we saw
00:17:22
for that first half of the second
00:17:24
session where sometimes that are too
00:17:25
high and sometimes too low heart rate,
00:17:27
but overall still not that bad. And if
00:17:30
we take a look at the one I wore on my
00:17:32
left wrist, we have even better results.
00:17:34
The correlation is now really good at
00:17:36
0.96
00:17:38
and most points are on or at least close
00:17:40
to blue line. And given the price point
00:17:42
of this device, which is probably around
00:17:45
50 bucks or so, but depending on when
00:17:47
you buy it, it might be even cheaper.
00:17:49
That's just really good. Now, there are
00:17:51
some reasons why it might be performing
00:17:52
well. One of them is, for instance, the
00:17:54
temperature outside. As you saw, it's
00:17:56
pretty hot inside now, 27.4 degrees, and
00:17:59
that's because it's hot outside. And
00:18:01
potentially, that increased temperature
00:18:03
leads to better blood flow through my
00:18:05
arms and therefore an easier signal for
00:18:07
the device to pick up on. I don't know
00:18:09
if this is really the case. This is
00:18:10
something I really want to investigate
00:18:12
at some point, see if there's some kind
00:18:13
of association between the performance
00:18:15
of a device and the temperature outside.
00:18:17
But overall, this looks pretty good. But
00:18:19
let's put this in the context of many
00:18:20
other devices out there. And you can see
00:18:22
that in this overview right here. And
00:18:24
you're familiar with this kind of
00:18:25
overview by now. So, we want the device
00:18:27
to be as far to the top right as
00:18:28
possible. And here I marked the Mi Band
00:18:31
10 on my left wrist in red. And it's not
00:18:34
that far from the Mi Band 10 on my right
00:18:36
wrist, which is right here. This is a
00:18:38
bit difficult to read, but I just want
00:18:40
to emphasize how far to the top right
00:18:42
these devices are. At least based on
00:18:44
this very initial test, they're doing
00:18:46
quite well compared to the competition.
00:18:48
But let's zoom in a bit so we can read
00:18:49
those labels better. And that zoomed in
00:18:51
views is played right here. So these are
00:18:52
just the devices with a correlation of
00:18:54
0.8 or higher with the Mi Band 10 on my
00:18:57
left wrist marked in red right here. And
00:19:00
a little bit lower, we have the Mi Band
00:19:02
10 on my right wrist. But both are
00:19:04
honestly doing quite well. They're doing
00:19:07
about as well as, for instance, the
00:19:09
Fibbit Charge 6, which is another
00:19:11
smaller device, the Huawei Watchfit 3
00:19:14
and the Huawei Watchfit 4, both of which
00:19:15
are quite good heart rate trackers as
00:19:17
well. I have more data for those two
00:19:19
than I have for the Mi Band 10. So, I
00:19:20
need to do more testing in the future,
00:19:22
but this initial test looks really good.
00:19:25
It's not quite as good as the Pixel
00:19:27
Watch 3 and also different Apple
00:19:28
Watches. These are really still the best
00:19:30
heart rate trackers out there, but for
00:19:32
the price, I'm honestly quite impressed.
00:19:34
So, so far that performance in terms of
00:19:36
heart rate tracking is pretty good for
00:19:38
the price. Now, this is an initial test,
00:19:40
but it's at least a good indicator of
00:19:41
what the device might be able to do.
00:19:43
There's still one exercise we need to
00:19:45
check, though, and that's running, and I
00:19:46
always use the Runa app for that, but
00:19:48
more on that later. I'll do the running
00:19:50
test tomorrow because I really need some
00:19:52
sleep. It's already quite late and I
00:19:54
already did quite a few exercises today.
00:19:56
So, we'll do that tomorrow. and also
00:19:57
take a look at the consistency of the
00:19:59
sleep stage tracking of the two Mi Band
00:20:01
10s because they should be tracking the
00:20:03
same sleep stages. If not, then they're
00:20:05
likely not very reliable. And we'll also
00:20:07
see if we can compare to an EEG device.
00:20:09
It actually measures my brain waves. But
00:20:11
with one night, it can sometimes go
00:20:12
wrong. And I'll give the word now to
00:20:14
Tomorrow Rob. So, I slept my first night
00:20:16
with the two Mi Band 10s and the results
00:20:18
are not great at first glance at least.
00:20:22
So, I can put the two sleep stages side
00:20:24
by side. So, this is one of the two
00:20:26
devices, and if I put the others side by
00:20:28
side, there's actually a big discrepancy
00:20:30
between the two. The moment I woke up is
00:20:33
more or less similar, but otherwise,
00:20:35
they don't appear to be much the same.
00:20:37
So, I'm actually going to try also to do
00:20:39
some kind of formal analysis, but it's
00:20:41
actually hard to get this data out. I'm
00:20:42
going to have to manually put it in some
00:20:44
Excel sheet, and then hopefully the data
00:20:46
quality of my EEG is good enough as
00:20:48
well. So, I'm going to have a look at
00:20:50
that as well. But first, want to go for
00:20:51
a run because it's already heating up.
00:20:53
It's already about 27° C again in my
00:20:56
room here and actually my working room
00:20:58
it's even hotter and we don't have air
00:21:00
con here in Europe. So I'm going to go
00:21:01
for a quick run before it gets too hot.
00:21:03
Then we're going to take a look at that
00:21:04
data and after that we're going to do a
00:21:06
more formal analysis on the sleep stage
00:21:08
data to see if they're consistent
00:21:09
between the two watches and if they
00:21:11
agree well with the EG if that data
00:21:13
quality is good enough. But first we're
00:21:15
going to go on that run. Well, first a
00:21:17
coffee and then we're going to go on
00:21:18
that run. But I'm actually not a runner
00:21:20
by training. I'm a cyclist by training.
00:21:22
I've been cycling for about 15 years or
00:21:24
so for sports and my whole life just for
00:21:26
commuting. And for running, I've always
00:21:28
struggled to make my running plans. And
00:21:30
that's where Runner comes in. I
00:21:31
affiliate with Runner. Runner is the
00:21:33
best running coach app out there. So, it
00:21:36
will make your whole running plan for
00:21:37
you if you have a certain goal or if in
00:21:39
general you're just looking to get into
00:21:40
running. And during the run, for
00:21:42
instance, on your Garmin device or your
00:21:44
phone, it will show you your pace and if
00:21:46
that pace is in the range or if you
00:21:47
should speed up or slow down. I really
00:21:49
love it. It's changed the way I run in a
00:21:51
very positive sense. It gives me sort of
00:21:53
a sense that I actually know what I'm
00:21:54
doing because before I would start way
00:21:56
too fast, way too much because I'm
00:21:58
generally fit because of cycling and
00:22:00
then for running I would always get
00:22:01
injured and it's now a lot better. So
00:22:03
after my coffee we're going to go on
00:22:04
that run together with runna and analyze
00:22:06
that data.
00:22:10
I'll try a bit of multitasking and
00:22:12
stretch at the same time. So during the
00:22:14
run I was looking at the watch and also
00:22:16
at my reference and they seemed to be
00:22:18
kind of okay. There was one moment where
00:22:20
I saw some deviation but maybe that was
00:22:22
just a very momentary difference. All
00:22:24
the analysis are running now so I can
00:22:26
show you. So all the analysis for the
00:22:28
heart rate are running right there. I'm
00:22:30
doing some analysis for the sleep
00:22:32
staging right there. Once I'm done
00:22:34
stretching, we'll look at the results
00:22:36
together. And the running results
00:22:38
actually look really good. So this is
00:22:40
the one on my left wrist right here. And
00:22:43
you can see that the red line of the Mi
00:22:45
Band 10 overlaps almost perfectly
00:22:47
honestly with the blue green line of the
00:22:49
reference device. So here I have nothing
00:22:51
to complain about. Let's take a look at
00:22:53
the other one. So the one on my right
00:22:55
wrist is also basically perfect. There
00:22:58
are some small deviations, but this is
00:23:00
so minor. I would have nothing to
00:23:02
complain about here. Here in the
00:23:03
beginning, you can see that when I
00:23:04
started it, it needed a moment to catch
00:23:06
my heart rate, but this is only a few
00:23:08
seconds. And after that, it's basically
00:23:11
perfect. But let's put a number on this.
00:23:13
Let's calculate that correlation and
00:23:14
look at that correlation plot. And here
00:23:16
we have that correlation plot for the Mi
00:23:17
Band 10 on my left wrist. And the
00:23:20
correlation is more or less perfect. So
00:23:22
a rounded correlation of 1.00. And given
00:23:25
that the correlation cannot be higher
00:23:27
than 1, 1.00 is close to perfect. There
00:23:30
are still tiny deviations, but this is
00:23:32
really really as good as it gets
00:23:34
usually. But let's take a look at the
00:23:36
one on my right wrist. This is also
00:23:38
basically perfect. We see that in the
00:23:40
beginning it needed a second to catch up
00:23:41
on my heart rate. That's why for a few
00:23:44
of the measurements the heart rate was
00:23:45
too low, but after that again super
00:23:47
close to the blue line. Not many watches
00:23:50
that I've seen perform better than this
00:23:51
device. But let's take a look at that in
00:23:53
a more detailed way by looking at the
00:23:55
performance of many devices I've tested
00:23:57
in the past. And here we have that
00:23:58
overview where again we want the devices
00:24:00
to be as far to the top right as
00:24:02
possible. And we have the Mi Band 10 on
00:24:04
my left wrist marked in red right here.
00:24:06
And the one on my right wrist is
00:24:08
actually very close. It's right here. So
00:24:10
about five devices down or so, but
00:24:13
they're both among some of the best
00:24:15
devices out there. And I honestly didn't
00:24:17
expect this beforehand. I don't know if
00:24:19
the current weather conditions and if
00:24:21
the way I ran, as in not too many
00:24:24
intervals, somehow benefited this
00:24:26
performance, but overall this looks
00:24:28
really good. And we also saw for the
00:24:29
other exercises that I did quite well.
00:24:31
But let's zoom in a bit so we can read
00:24:32
those labels better. And here we have
00:24:34
that zoomed in view. in this case, just
00:24:36
the devices with a correlation of 0.9 or
00:24:38
higher. And the Mi Band 10 on my left
00:24:41
wrist is the best performer out of all
00:24:43
devices I've tested. Now, again, this is
00:24:45
for a single run under sunny conditions,
00:24:48
but still very good. And the one on my
00:24:50
right wrist basically performed the
00:24:52
same. So, we at least have one replicate
00:24:54
measurement on both of my wrists. I'm a
00:24:56
bit afraid, but I don't think this is
00:24:57
the case, that maybe the Mi Band 10 is
00:25:00
searching for Bluetooth signals of heart
00:25:02
rate and picking up on them and using
00:25:04
them without letting me know. I don't
00:25:05
think this is really the case. That
00:25:07
could be the one deviant explanation for
00:25:09
why it's doing so well. But assuming
00:25:11
that's not the case, it's doing really
00:25:13
well. And the heart rate monitor within
00:25:15
the Mi Band is able to measure my heart
00:25:17
rate quite well. And for the price, this
00:25:19
is basically the best device out there.
00:25:21
The only close contender is the Huawei
00:25:23
Band. So, for instance, the Huawei Band
00:25:24
9 did quite well on me for running about
00:25:27
the same as the Mi Band 10. So, both of
00:25:29
these are quite cheap devices. With the
00:25:31
Huawei Band, you get a bit of a bigger
00:25:33
screen, but otherwise, I'm really
00:25:35
content with the Mi Band 10. It's doing
00:25:37
about the same as, for instance, the
00:25:39
Whoop MG that I wear on my biceps or
00:25:42
different Apple watches. Now, I'll do
00:25:44
more testing. I hope to also give it to
00:25:46
Raphael for some testing or maybe
00:25:47
somebody else to independently test if
00:25:50
the Mi Band 10 is good at heart rate
00:25:51
tracking. But this is a good first
00:25:53
indication. I don't know what you think.
00:25:55
I didn't expect this. Maybe you have
00:25:57
different experience with it. Actually
00:25:58
want to look at the sensor of the Mi
00:26:00
Band 10 at some point and compare to the
00:26:02
previous Mi Bands. I didn't do much
00:26:04
running before, so I didn't do a lot of
00:26:06
testing with older Mi Bands for running.
00:26:08
But as a first indication, this is very
00:26:10
good. So those are really surprisingly
00:26:12
good results. I now want to take a look
00:26:15
at this sleep stage tracking, but that's
00:26:16
going to take me some time to both
00:26:18
process the data, actually get the data
00:26:20
into my computer. There's going to be a
00:26:21
lot of manual work. We're going to do
00:26:23
that analysis. First, I have to eat
00:26:24
something, but then I'll get back to
00:26:25
you. I analyzed all the sleep data, and
00:26:27
we're going to start by looking at how
00:26:29
the Mi Band 10 performed compared to the
00:26:31
reference device I have, which is the
00:26:33
Zmax EG headband, which can actually
00:26:35
measure my brain waves, and is
00:26:37
specifically designed for sleep
00:26:38
tracking. And here you can see how the
00:26:40
Mi Band 10, the black version compares
00:26:43
to that reference device with the sleep
00:26:45
stages is measured by the reference
00:26:47
device on top and those according to the
00:26:49
Mi Band 10 on my left wrist here on the
00:26:51
left. Now each column here sums to 100%.
00:26:55
Meaning that we can see what percentage
00:26:56
of each of the sleep stages according to
00:26:58
the reference was detected as a sleep
00:27:00
stage by the Mi Band 10. And if they
00:27:02
would perfectly agree, all values along
00:27:04
the diagonal here should be 100%. Now I
00:27:06
should mention two things here. There
00:27:08
were some small data issues with the
00:27:09
reference device, mostly leading to more
00:27:12
awake moments. So, we're going to ignore
00:27:13
the awake column right here. And second,
00:27:16
this is just for one night, so we cannot
00:27:18
draw any definitive conclusions. But I
00:27:20
do think the patterns are pretty clear.
00:27:22
Now, first of all, for this Mi Band, the
00:27:24
deep sleep agreement was pretty good at
00:27:26
about 90%. However, the light sleep
00:27:29
agreement and the RAM sleep agreement
00:27:31
both aren't very good at about 50%
00:27:33
agreement. and instead a lot of it was
00:27:36
either predicted as light sleep in the
00:27:37
case of REM or as deep sleep or REM
00:27:40
sleep in the case of light sleep. So not
00:27:42
looking that good honestly. But what is
00:27:44
even more surprising and worrying in a
00:27:46
way is how much worse the other Mi Band
00:27:48
performed. So that's this one right
00:27:50
here. This is the Mi Band on my right
00:27:52
wrist. We have pretty poor deep sleep
00:27:54
agreement where much of it was detected
00:27:56
as light sleep instead. Again, otherwise
00:27:58
being predicted as deep sleep or RAM
00:27:59
sleep and also really bad RAM sleep
00:28:02
agreement. And the fact that one agrees
00:28:04
a bit better with the reference than the
00:28:06
other also means that the two amongst
00:28:08
themselves likely don't agree very well.
00:28:10
And I want to show you that by just
00:28:11
looking at the knights themselves. And
00:28:13
here we have the actual night of data
00:28:15
with the reference device on top. So if
00:28:17
the clock time along the horizontal axis
00:28:19
and the sleep stage is on the vertical
00:28:20
axis. And on the bottom a similar plot
00:28:23
but now for the Mi Band 10. And as you
00:28:25
can see the agreement isn't that great
00:28:28
honestly. So in percentages we saw that
00:28:30
a lot of the deep sleep detected by the
00:28:32
EEG device was also detected by the Mi
00:28:34
Band 10. There are three main deep sleep
00:28:37
segments and all of these were more or
00:28:39
less detected by the Mi Band 10, but a
00:28:41
lot of extra deep sleep is detected all
00:28:43
throughout the night and this isn't very
00:28:45
realistic. And also the RAM sleep is
00:28:48
just randomly spread out throughout the
00:28:50
night. Normally you go through sleep
00:28:52
cycles, each one ending in RAM sleep. So
00:28:53
I likely had 1 2 3 4 five sleep cycles.
00:28:59
And you can clearly see this based on
00:29:00
the EG device. So there's some deep
00:29:02
sleep and light sleep followed by RAM.
00:29:04
Deep sleep and light sleep followed by
00:29:06
RAM. Deep sleep light sleep followed RAM
00:29:08
etc etc. And you just cannot see this
00:29:11
based on the Mi Band 10 data. And if you
00:29:13
look at the other Mi Band 10, so the one
00:29:14
on my right wrist, we see a very
00:29:17
different pattern. So again, it's not
00:29:20
good and very different. And so there's
00:29:22
much less deep sleep here in the
00:29:23
beginning of the night. Also, the time I
00:29:25
fell asleep is a bit shifted. Now, this
00:29:27
shift I actually allow for. So, I allow
00:29:29
in my script for it to find the best
00:29:31
match between the reference data and the
00:29:34
Mi Band 10 by shifting plus or minus 15
00:29:37
minutes because there will always be
00:29:38
some discrepancies. And with the best
00:29:40
fit that it found, it really doesn't
00:29:42
agree very well with the EG device. So,
00:29:45
it detects a lot of deep sleep near the
00:29:46
end of the night where I normally have
00:29:48
very little deep sleep. And also the RAM
00:29:50
sleep just agrees very poorly with the
00:29:53
EG device. So overall I'm not very happy
00:29:56
with this performance and I can actually
00:29:58
show you that there are many devices
00:30:00
that perform better and you can actually
00:30:01
see that in this overview right here. So
00:30:04
this is the performance in terms of
00:30:05
sleep stage tracking for all the devices
00:30:07
I've tested in the past or many of them
00:30:09
at least where the further to the right
00:30:11
and the higher devices, the better is
00:30:13
its agreement with the reference device.
00:30:15
So, we have the average agreement over
00:30:16
the individual sleep stages along the
00:30:18
horizontal axis and the worst sleep
00:30:20
stage agreement along the vertical axis.
00:30:22
Now, I actually didn't plot the Mi Band
00:30:24
10 in this overview yet, but we can do
00:30:26
that. And if we're being very generous,
00:30:29
we can take the best agreement right
00:30:31
here. So, we can calculate the average
00:30:33
agreement by summing these three numbers
00:30:37
right here and dividing it by three. So
00:30:40
we get 65%
00:30:42
and the worst sleep stage is about 52%.
00:30:45
So if we take 65 and the other number
00:30:49
was 52 we would end up somewhere around
00:30:53
here. So actually doing pretty okay but
00:30:56
as we saw ending up around here would be
00:30:58
a bit over optimistic. If we take the
00:31:01
other percentages, so those were these
00:31:03
ones right here, we would end up, let's
00:31:07
see, with an average agreement of 41%
00:31:10
and a worst of 36. So 41
00:31:15
and 36 would be somewhere around here,
00:31:18
somewhere around some Huawei devices, a
00:31:21
little bit worse than what I had for the
00:31:22
Mi Band 9 potentially. And where's the
00:31:25
Mi Band 9 Pro? Right here. So these
00:31:27
ended up right here. But we can also
00:31:28
take the average of those two results
00:31:30
and that will probably be more fair and
00:31:32
that's where I'll place it for now. Let
00:31:33
me quickly calculate that. So if we
00:31:35
assume the average is true, we would
00:31:38
over the three sleep stages which is now
00:31:40
an average on average. So this is not
00:31:42
perfect. I can recalculate for my
00:31:45
long-term testing. We would end up with
00:31:47
an average of an average of about 53
00:31:49
over the three sleep stages. And the
00:31:51
worst sleep stage right here would be
00:31:53
about 44. So we would have 53 on average
00:31:56
and about 44 as the worst sleep stage.
00:31:59
If we put these two numbers in that
00:32:00
overview right here, we would have 55.
00:32:04
So roughly 53 right here, let's say, and
00:32:07
then 45 would end up right here
00:32:12
somewhere. Maybe a little bit lower. So
00:32:15
right here, this is where the Mi Band 10
00:32:16
would end up. We can actually make it
00:32:20
readable. Okay, here we are. This is
00:32:22
sort of the temporary overview we would
00:32:24
end up with. So we have the Mi Band 10
00:32:26
right here which had a 54% average of
00:32:30
average. So not perfect in terms of
00:32:32
testing, but if I were to recalculate
00:32:33
it, we would mostly end up with the same
00:32:36
thing. And then 44% along the other
00:32:39
axis. And you can at least see that for
00:32:40
this very initial test, it's not that
00:32:42
far away from the Mi Band 9, the Mi Band
00:32:45
9 Pro, and the Mi Band 8 actually did
00:32:48
quite a lot worse in my testing. This
00:32:50
might be a fluke, but all of them are
00:32:52
amongst the lower performing devices
00:32:54
right here. So, not doing very good. The
00:32:56
best sleep stage trackers out there are
00:32:58
the Apple Watch. If you get any more or
00:33:00
less recent version, you'll get pretty
00:33:02
good sleep stage tracking. Even with
00:33:04
something like the Apple Watch SE from
00:33:06
2022, which you can probably get
00:33:07
refurbished for a pretty good deal, and
00:33:09
you'll get good heart rate tracking. The
00:33:11
eight sleep pot, which is my favorite
00:33:13
sleep improvement device on these hot
00:33:15
days. This really helps me sleep a lot
00:33:17
better because it can actively heat and
00:33:19
cool each side of the bed independently.
00:33:21
It's been a godsend for my sleep. It is
00:33:24
very expensive though, so only get it if
00:33:26
you can really afford it. If you want
00:33:28
the best discount possible, my affiliate
00:33:30
link is down here or up here and you'll
00:33:32
be supporting the channel at the same
00:33:33
time. Then we also have the Aura Ring
00:33:36
right here, which is doing pretty well.
00:33:38
And finally, there's the NUA, now called
00:33:40
Sleep 2 app, which is specifically
00:33:42
designed for sleep tracking. Also pretty
00:33:44
good. You'll need an extra device to go
00:33:46
with it though because it's just an app.
00:33:48
And then in the second tier of devices,
00:33:50
we have different Google and Fitbit
00:33:51
devices which are also pretty good and
00:33:53
you can get some Fitbits for a pretty
00:33:55
decent price. You get the same sleep
00:33:57
stage tracking no matter if you have
00:33:58
like a very old Fitbit Charge 2 or a
00:34:01
newer Fitbit Charge 6 or a Pixel Watch.
00:34:04
And finally, there's the Whoop Strap,
00:34:05
which is one of my favorite allround
00:34:07
devices. I also have an affiliate link
00:34:09
for that up here or down here and you
00:34:11
can check out my full review as well.
00:34:12
But overall for sleep stage tracking,
00:34:15
the Mi Band 10 isn't amazing. But let's
00:34:17
now get to my overall conclusions. Okay,
00:34:20
so that was a lot of data on the Mi Band
00:34:22
10. Actually, two Mi Band 10s and the
00:34:24
results are super interesting in my
00:34:26
opinion and actually better than I
00:34:27
expected. Wait, let me put you down for
00:34:29
a second. In terms of heart rate
00:34:31
tracking, the Mi Band 10 actually did
00:34:33
pretty good or actually very good, at
00:34:35
least for the price point. If you get it
00:34:38
for, let's say, 40 or 50 bucks, it's
00:34:40
really a good performer. At least based
00:34:42
on this initial testing, it's doing a
00:34:44
lot better than many quite a bit more
00:34:46
expensive devices. Now, you get a small
00:34:48
screen and it's maybe not the best sort
00:34:51
of smart watch out there, but in terms
00:34:53
of heart rate tracking, at least on me,
00:34:55
it's doing surprisingly well. I'll also
00:34:57
give it to Rafael, my colleague, for
00:34:59
testing, or maybe another person because
00:35:01
it would be very interesting to see if
00:35:03
these results are replicable on a second
00:35:05
person. And of course, this was a very
00:35:06
initial test, just doing one or two of
00:35:09
the same exercises. So, we need to do
00:35:11
many, many more to see if these results
00:35:14
are consistent over a longer time
00:35:16
period. But I'm happily surprised given
00:35:18
the price point and even if the
00:35:20
performance is actually a bit worse in
00:35:22
reality, you can't really go wrong if
00:35:24
you want sort of basic heart rate
00:35:26
tracking or maybe even very good heart
00:35:28
rate tracking. The sleep stage tracking
00:35:30
on the other hand, I'm not very excited
00:35:32
about, but this is sort of what I
00:35:33
expected. It would take a lot of money
00:35:36
and effort for Xiaomi to create a better
00:35:38
sleep stage tracking algorithm. Usually
00:35:40
across their entire lineup, a single
00:35:43
brand has the same sleep stage tracking
00:35:44
algorithm because you need to create a
00:35:46
big data set of reference data and data
00:35:49
with the device to actually train that
00:35:50
model. It's actually sort of an AI or
00:35:53
machine learning task. You've heard
00:35:54
these terms thrown around a lot and for
00:35:56
that you need a lot of reference data or
00:35:58
training data similar to how for
00:36:00
instance Google developed their large
00:36:01
language models or chat GPT was
00:36:03
developed. You need a lot of training
00:36:05
data for that to become a good model.
00:36:07
And the same is true for sleep stage
00:36:09
tracking. You need a lot of data with
00:36:11
both the reference device measurements
00:36:13
and the measurements with the actual
00:36:15
device you're trying to train for. So
00:36:17
the device itself can actually learn how
00:36:19
to predict your sleep stages. And this
00:36:21
will always be a relatively difficult
00:36:23
task with a decent amount of data
00:36:25
required. And I suspect that Xiaomi
00:36:27
hasn't collected that type of data. So
00:36:29
who's this device for? Well, based on my
00:36:31
initial testing, somebody who wants to
00:36:33
track their heart rate during their
00:36:35
exercises doesn't care too much about
00:36:38
the app because I don't really like the
00:36:40
Mi Fitness app that much compared to
00:36:42
some of the competition. I still think
00:36:44
for instance, the Aura Ring or the Whoop
00:36:46
Strap definitely provide a better app
00:36:48
experience with more interpretable data
00:36:50
also on your recovery. Both also have
00:36:52
much better sleep stage tracking. So, if
00:36:55
you're interested in your health and
00:36:56
sleep tracking, then I wouldn't get the
00:36:58
Mi Band. But if you just want heart rate
00:37:00
tracking, you want to look at your heart
00:37:02
rate during your exercise and see if
00:37:04
you're going too hard or not, then it
00:37:06
might be a valid choice. And given the
00:37:08
price, it's actually not bad. Of course,
00:37:10
think about e-ways. Do you actually need
00:37:12
this device or is it better to buy a
00:37:14
better device now instead of the cheaper
00:37:16
one now and then in half a year
00:37:18
upgrading again? But if you don't have a
00:37:20
big budget and you are going to use this
00:37:22
device for quite a while, it might
00:37:24
actually be a good option. But I'll keep
00:37:25
you updated once I do my retesting and
00:37:28
my long-term review. Now, if you do
00:37:30
decide to get the Mi Band 10, a Whoop
00:37:33
strap, an Aura Ring, an HLE pod, another
00:37:36
device, or anything at all on Amazon for
00:37:38
that matter, even something as small as
00:37:40
toilet paper. You want to support the
00:37:42
channel and save some money, there are
00:37:44
different affiliate links in description
00:37:45
below that give you the best discount
00:37:47
possible. If you're into running, I
00:37:49
really recommend the Runna app, which
00:37:51
creates running plans for you and live
00:37:53
coaching during your run. Or if you want
00:37:55
to track your glucose levels and want to
00:37:57
find out which foods cause big glucose
00:37:59
spikes for you personally, I really like
00:38:02
the Levels app. Both have an affiliate
00:38:03
link down below, giving you the best
00:38:05
deal possible. Now, given that you
00:38:06
watched this whole video on the Mi Band
00:38:08
10, I think you might like this video on
00:38:11
the Whoop Strap or this video on the
00:38:13
Huawei Watchfit 4 Pro.