The new Brain Age feature starts rolling out on October 19 for Muse 2, Muse S and Muse S Athena. It delivers weekly readings, allowing users to track changes over time.

How Muse Brain Age works

The concept is fairly simple. Muse uses four EEG sensors positioned around the forehead and behind the ears to record electrical activity in the brain. An AI model then compares those patterns with age-related changes observed in other users.

The result appears as a difference in years rather than an absolute brain age. You might see that your brain is tracking three years younger than your actual age, for example, or two years older.

There are two parts to the calculation. Alongside regular EEG recordings, Muse uses four short cognitive tests covering processing speed, spatial memory, impulse control and selective attention. The app shows how each component contributes to the overall estimate.

Getting your first result takes some patience. You’ll need at least ten minutes of qualifying daytime EEG sessions on seven separate days, plus all four cognitive tests. Sleep recordings don’t count, despite Muse’s longstanding focus on sleep tracking.

After that, three qualifying EEG days per week are enough to maintain the estimate. Updated Brain Age scores arrive every Monday.

How accurate is it?

So is this a gimmick or is it accurate? That is the obvious question.

The company says it has been working on brain age estimation for some time. We covered its plans to introduce the feature earlier this year, following research involving thousands of at-home EEG recordings.

Muse says its system can estimate a person’s age from brainwave readings with an average error of 3.8 years. So if you’re 50, the estimate could be several years higher or lower. That’s a reasonable result for consumer EEG technology.

Worth mentioning is that there’s a bit of fluctuation in the results. Muse says your estimated brain age can vary by around 1.9 years from one week to the next. That’s why the company recommends looking at how the readings develop over several months, rather than focusing too much on any single week. The feature is also not designed to detect dementia or cognitive decline.

Available on existing headbands

Existing Muse owners won’t need new hardware. The feature supports Muse 2, Muse S and Muse S Athena, all three of which we’ve reviewed over the years. Athena already offers detailed cognitive tracking, so Brain Age fits well alongside its existing measurements.

Everyone gets their first reading free. However, continued weekly monitoring requires Muse Premium.

For Muse, this is another way to put the EEG data collected by its headbands to use. And for existing owners, it’s a new feature they can try without buying another device.

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So this is not some obscure developer API tweak. Buy a new Withings scale today, try to send your readings into Apple Health, and you could suddenly find a subscription standing in the way.

Withings+ becomes required on the Start for Free API plan from October 12, 2026.

Withings accounts created after that date will need a membership to share health data with a free-plan app, including apps that are already live.

Accounts created before that date are unaffected, and Enterprise lifts the requirement for specific use cases.

The new rule started on October 12

Withings has added the change to its developer API plans. Accounts created prior to October 12 are exempt, so existing users should keep their current access.

The important part is what happens to new accounts. Withings specifically says users cannot get around the Withings+ requirement by sharing data through Apple Health or Google’s health ecosystem instead.

That means the restriction reaches ordinary consumers, not just developers building apps around Withings data. A new user could buy a Withings scale, pay for the hardware, and still need Withings+ if they want those measurements automatically sent elsewhere.

Some Withings users have already reported seeing exactly that behaviour after setting up a Body scale. When Apple Health export was enabled, the Withings app displayed a Withings+ subscription screen.

Withings+ currently costs $9.99 per month or $99.99 per year in the US. That is a sizeable extra cost for someone who mainly wants their weight, body composition or other measurements to appear alongside data from their Apple Watch or another device.

This changes the value of Withings hardware

Withings has always made particular sense for people who mix devices from different brands. You might use a Withings scale at home, an Apple Watch on your wrist and Apple Health as the place where everything comes together.

Devices such as BodyScan 2 collect a wide range of body measurements, while watches such as the ScanWatch 2 add activity, sleep and heart-rate data. Being able to move those readings between ecosystems is an important part of the appeal.

We also saw Withings push further in this direction earlier this year when Samsung and Withings expanded their health data sharing. The whole point of integrations like these is that people increasingly use health hardware from several different companies.

Putting basic data export behind Withings+ changes that equation. It does not make the hardware less capable, but it adds another recurring cost that new buyers need to know about.

Withings says subscription revenue helps fund clinical validation, regulatory work and the infrastructure behind its health platform. That argument is easier to understand when Withings+ is paying for additional analysis and services.

We have already seen the company put more advanced features behind the subscription, including the StethO Sense feature for BeamO. Charging for extra analysis is one thing, though. Charging new users to move their own measurements into Apple Health is quite different.

Existing users appear unaffected for now, which softens the immediate impact. But anyone buying into the Withings ecosystem from October 12 onward now needs to factor Withings+ into the cost if cross-platform data sharing matters to them.

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Most companies chasing needle-free glucose are trying to make the wrist work. We’ve already seen WHOOP explore non-invasive glucose monitoring, while Garmin has patents around estimating HbA1c using optical sensors. Verily is taking a completely different route by changing where the measurement happens.

Verily is basically asking a different question: why use the wrist at all?

Why the eyelid makes sense

According to the filing, the blood vessels in the palpebral conjunctiva, the tissue lining the inside of the eyelid, lie less than 100 micrometres below the surface. Their depth is also fairly consistent from person to person.

That is important for an optical sensor. A short, predictable path to the blood leaves less in the way. At the wrist, light must pass through skin and tissue, with blood vessels at varying depths and plenty of other signals adding noise.

The lower eyelid also provides a natural pocket to hold the device in place. Verily describes a soft, curved, flexible sensor that sits between the eyeball and the lower eyelid, with its optics facing the eyelid tissue. One example in the drawings measures around 18 mm long. The filing also mentions smaller versions, with the goal of keeping the sensor largely or entirely hidden once fitted.

Infrared light and a lot of tears

Rather than relying on a chemical sensor, the device uses short-wave infrared light. Tiny LEDs shine light into the blood vessels in the eyelid while a photodetector measures what reflects back. Because glucose absorbs light differently across the infrared spectrum, the choice of wavelengths is central. The patent covers 900 to 1,700 nm in broad terms, with more specific examples in the 1,300 to 1,700 nm range.

The obvious problem is tears. An optical sensor under the eyelid sits in a constant tear film, which can interfere with the reading. Verily addresses this on several fronts. The sensor can use one wavelength range to pick up the glucose signal and a second to account for water, then subtract the water signal from the first reading.

The hardware helps as well. The casing can have a hydrophobic surface that repels tears around the optical components. The filing also describes an oil-based coating between parts of the device and the eyelid to reduce the effect of the tear film. A good share of the patent is devoted to keeping water out of the measurement.

Built to talk to your phone or watch

Power and data are handled wirelessly. Verily describes NFC for communication and potentially for wireless power, so the sensor may not need a conventional battery. Bringing a phone close to the eye would allow it to communicate with the sensor, with Bluetooth and Wi-Fi listed as alternatives.

The patent names smartphones, tablets and smartwatches as devices that could connect to it. The sensor itself would not be a traditional wearable, yet it could fit into a broader wearable health setup.

Glucose is not the only target, either. The filing states that the same approach could detect other substances in the blood, including cholesterol, potassium, iron, magnesium, lactate and insulin. Patent applications are written broadly, though, and naming a substance is a long way from measuring it reliably.

So this is not a sign that a needle-free Verily CGM is just around the corner. What makes the filing worth watching is the location. If optical glucose sensing does eventually work reliably, the sensor that gets there may not sit on your wrist at all.

Source: USPTO

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The study, out of Tohoku University, was published in iScience at the end of August. It’s since made the rounds on various biohacking forums, where people are already asking whether their own neck stimulators and TENS ear clips might pull off the same trick.

But before anyone goes cranking up the intensity, it’s worth taking a closer look at what the researchers actually did.

Stimulation after practice, not during

The mice were trained on a horizontal optokinetic response task, a fancy way of saying they learned to track moving stripes with their eyes. It’s similar to the reflexive eye movements you make when standing on a platform watching a train go by. This kind of learning relies on the cerebellum.

The team applied vagus nerve stimulation after each training session, not during it. During training itself, it had little effect. The benefit emerged over the following days, with stimulated mice performing better. As Professor Ko Matsui put it, “the key point is that VNS was delivered only after training.”

That suggests the period after practice is a window when the brain is still cementing a skill. According to the researchers, the stimulation makes the brain more open to lasting change during that time.

The blood vessel twist

Most earlier research has focused on how vagus nerve stimulation alters neurotransmitter systems. This study points in a different direction. The team measured blood volume near the cerebellar flocculus, a region involved in this eye task. A single burst of stimulation caused a brief dip in blood volume followed by a rise. Repeated sessions turned that into a rhythmic rise and fall.

Mice with larger oscillations tended to score better on day five. That is a correlation rather than proof, though. The study summary is clear that it does not show the vessel rhythm caused the better learning.

Your neck gadget is a different story

Here’s the catch for anyone hoping for a learning hack. The mice had a small cuff electrode attached directly to the vagus nerve in the neck, which is implanted stimulation. Consumer devices send pulses through the skin. The study did not test those or breathing exercises.

The wider research picture is mixed too. A 2024 study in rats found stimulation paired with training didn’t improve learning across motor, speech sound and memory tasks. That team stimulated during training while the Tohoku group waited until afterwards, so the two results aren’t a straight comparison.

Neck-worn stimulators are sold for stress and sleep, not learning. When I reviewed Pulsetto it helped me fall asleep faster. The newer Pulsetto Fit adds longer battery life and a wave-like stimulation mode. Kineon’s Calm+ also sits around the neck. All of them are pitched at calm rather than mastering a new skill.

If you are more curious about what your brain is doing, the Muse S Athena tracks brain states and sleep. It reads rather than stimulates, which is a very different job.

So the takeaway is about timing more than gadgets. The period right after practice might matter more than we think. Whether any device can make use of that in people is a question for future studies.

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A newly published Google patent describes a system that monitors what happens after an initial cardiac arrhythmia event, looks for patterns in subsequent episodes and uses those patterns to predict when another event is likely to occur. The US patent application, numbered US 2026/0294263 A1, was published at the start of this month.

The watch would learn your own pattern

The basic idea is actually pretty simple. A wearable detects an initial cardiac arrhythmia event using its biometric sensors. The patent repeatedly uses atrial fibrillation as an example, although its claims cover cardiac arrhythmias more broadly.

That first event then triggers an observation period. During this window, the wearable continues collecting heart data and records additional arrhythmia events.

The system looks at their timing and frequency to see whether there is a pattern specific to that person. If there is, Google proposes using it to generate a prediction of when a future event may occur.

So this is not simply a general risk score telling someone they are more likely to develop AFib at some point. The patent describes learning from actual arrhythmia events and looking for temporal patterns that could help forecast another one. For example, if someone’s episodes repeatedly occur at certain times or tend to appear at fairly regular intervals, that information could potentially become part of the prediction.

This goes beyond today’s AFib alerts

Current wearables can already look for signs of AFib. Google’s own devices are part of that. I recently looked at how AFib detection works on Fitbit Air, where heart rhythm and movement data collected while the user is still can trigger an irregular rhythm notification.

Pixel Watch goes further by offering ECG hardware on compatible models. But these features are still fundamentally looking for something that is happening or has already happened.

Prediction flips that around. Rather than asking whether the wearer’s rhythm appears irregular now, the system starts asking what might happen next.

It also fits well with where Google has been taking its health platform lately. Health Guardian already uses existing wearable data to identify longer-term patterns linked to blood pressure and insulin resistance, rather than relying on dedicated sensors that directly measure either one.

AFib prediction would push that idea further. The sensors gather the raw signals, but more of the value comes from interpreting patterns across time.

But patents are not product roadmaps. Companies routinely patent technologies that never appear in a commercial device, or that arrive years later in a substantially different form.

There would also be a much higher bar for something that claims to predict a future cardiac event. Detecting signs of AFib is already a regulated health feature. Telling someone that another episode may be approaching would need convincing clinical validation before Google could put that sort of warning on millions of wrists.

Still, the direction is worth watching.

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The study, published in BMC Medicine, analysed 1,290 people from the Northern Finland Birth Cohort. Participants were aged 33 to 35 and were asked to wear an Oura Ring for two weeks while also completing established questionnaires covering anxiety and depression symptoms.

The pattern shows up in several metrics

People reporting moderate-to-severe anxiety tended to spend less of the night in REM and deep sleep and more time in light sleep. Similar differences appeared among participants whose questionnaire results indicated depression and anxiety symptoms.

And it was not just sleep stages. Those groups also tended to have a higher heart rate during sleep, lower nighttime HRV and lower levels of physical activity during the day.

None of those findings on their own are particularly surprising. Poor sleep, reduced activity and changes in autonomic nervous system activity have all been associated with mental health before. What makes this study more interesting is that all of these signals were picked up passively by an ordinary consumer smart ring while people went about their normal lives.

HRV is particularly worth watching here. We have written before about how wearables use HRV to track recovery and stress, and lower readings can show that the body is dealing with some kind of additional load. The problem is that HRV cannot tell you what that load actually is.

Alcohol, illness, poor sleep, training, stress and plenty of other things can all move the number. So seeing low HRV on an Oura Ring obviously does not mean someone has depression or anxiety.

The study becomes more useful when those signals are looked at together. Lower HRV combined with higher sleeping heart rate, less deep and REM sleep and reduced daytime movement starts to create a broader physiological and behavioural pattern rather than relying on any single measurement.

This was not Oura’s latest hardware

The researchers actually used the second-generation Oura Ring. Which makes the results a little more interesting. The study was not relying on some new sensor or experimental mental health feature. It was using fairly basic metrics that smart rings and watches have already been collecting for years.

Participants also did not receive feedback from the ring during the study, so their behaviour was not being nudged by readiness scores or recommendations in the Oura app. The researchers were essentially looking at the raw pattern left behind by sleep, nighttime heart rate, HRV and movement.

There are still some big limitations. This was a cross-sectional study, so it shows an association at one point in time rather than demonstrating that these wearable changes predict worsening mental health. The participants were also all around the same age and came from the same Finnish birth cohort.

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Huawei’s Watch GT 7 product page says the feature requires between three and 14 days of continuous wear. It arrives through an OTA update and users need to join the study through the Huawei Research app.

How the diabetes risk study works

So how does this actually work?

The Watch GT 7 uses pulse-wave signals collected by its PPG sensor, so the same tech that monitors hear rate. It then combines this with information such as age, sex, height and weight. After enough data has been collected, the system produces a diabetes risk assessment.

Now Huawei is not claiming the watch measures glucose directly. There is no glucose value in mmol/L or mg/dL, and the company says the feature cannot be used to monitor diabetes treatment. But it could flag up an issue that you could investigate further.

The rollout appears to be research-led rather than a standard health feature available everywhere. In Malaysia, Huawei says the study is initiated by Universiti Malaya, while availability depends on region.

We already flagged the high blood sugar risk assessment when looking at the Watch GT 7 generation. The latest regional rollout gives a clearer picture of how it actually works.

Huawei has explored similar ideas before. Earlier this year, the company brought diabetes risk alerts to the Watch GT 6 Pro, again using smartwatch sensor data to identify patterns linked with elevated risk.

The Watch GT 7 takes that approach into Huawei’s latest mainstream watch range. Both the standard GT 7 and GT 7 Pro are included.

Huawei is also working on a blood sugar device

The more interesting context is what Huawei has said about its next step. Just a few days ago Huawei Consumer Business Group CEO confirmed that the company plans to release a blood sugar testing device. Apparently, it’s been work in progress for the past four years.

Huawei has not said what that device will look like or how it will measure blood sugar. It could be a watch, another wearable or a separate health product.

Huawei is clearly pushing further into blood sugar-related health tracking, both through existing smartwatch sensors and new dedicated hardware. Hopefully, we’ll see exciting developments here in the coming months.

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The comment came from Huawei Consumer Business Group CEO He Gang during a recruitment event at Peking University. He said Huawei plans to release the device and that the technology behind it took four years to get to a point the company considered acceptable and ready for industrialisation.

That is about as close as Huawei has come to saying something new is actually on the way. The problem is that He Gang stopped there, so we still don’t know what the device looks like, how it works or whether it is even something you wear on your wrist.

Non-invasive glucose monitoring?

The obvious guess is that Huawei is working on some kind of non-invasive glucose monitoring. We already have finger-prick meters and invasive continuous glucose monitors, so it would be a bit strange to spend four years on research just to come up with another version of something that already exists.

Huawei still hasn’t actually said that, though. Gang didn’t explain how the technology works, whether it tracks glucose continuously or even whether the device sits on the wrist. But reading between the lines, non-invasive sensing looks like the most likely direction.

A wearable also feels like the obvious fit. Huawei has been pushing harder into health features for years, and the latest Watch D3 already uses a tiny inflatable airbag in the strap to take proper oscillometric blood pressure readings.

So Huawei clearly isn’t afraid of building unusual hardware around health tracking. Whether this blood sugar device ends up as a watch, another type of wearable or something separate is still unknown, but a conventional glucose meter would be the least interesting explanation.

There have been hints before. A report in September 2025 claimed Huawei was developing an advanced blood sugar monitoring wearable for 2026, although that came from a Weibo tipster rather than Huawei itself. At the time there was very little to back it up.

Our takeaway

This week’s comment carries considerably more weight than previous rumours because it comes directly from the head of Huawei’s consumer business. It also changes the wording from something being researched to something Huawei plans to release.

Separately, a few Huawei watches can already assess a user’s risk of elevated blood sugar, but that system doesn’t measure an actual glucose value. The recently launched Watch GT 7 series, for example, supports high blood sugar risk assessment in compatible markets. But again, it isn’t a glucose monitor.

So this is one to keep an eye on. There is still plenty of room between ‘ready for industrialisation’ and a product sitting on a shop shelf. Regulatory approval would also become a major part of the story if Huawei intends to market the device as something that genuinely measures blood glucose.

Sources: IT Home, Huawei Support, Weibo, Huawei Central

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The patent was published on September 17 and describes a miniaturized impedance plethysmography sensor (IPG sensor), built into a computing device. The drawings make the wearable angle pretty obvious too. One example is a smartwatch, while others show small finger-worn devices and even other types of electronics.

Your fingertip becomes part of the sensor

The basic idea is quite neat. Google places a set of miniature electrodes underneath the fingertip, with two used to send a tiny electrical excitation signal through the tissue and another two used to measure the resulting electrical response.

Blood flowing through the finger changes its electrical impedance. By tracking those changes, the system can produce a pulsatile waveform that reflects the blood pulse, and Google says that signal can then be used to determine blood pressure or a proxy for blood pressure. The patent’s process diagram boils the whole thing down to generating IPG data, deriving the pulsatile signal and then estimating blood pressure from it. 

And Google clearly has smartwatch use in mind. Figure 6A shows the system incorporated into a watch worn on the wrist, with the sensing area positioned on the watch body where a finger could be placed against it. Earbuds are another option. As well as smartphones.

That’s not the only idea

And this is not even the only recent Google patent dealing with the problem. A separate application published last month describes a small finger cuff containing an inflatable bladder, multiple pressure sensors and optical sensors. 

That system would inflate around the finger while an array of barometric sensors maps pressure around the digital artery. But as you can see from the image below, it’s not exactly a discreet smart ring.

Optical sensors simultaneously measure the pulse, and the device combines those signals to calculate blood pressure. The patent’s flow diagram specifically shows inflation, pressure mapping, optical measurements and the final blood pressure estimate as parts of the process. 

Where this fits with Google’s plans

It is worth noting that neither patent names a Pixel Watch or Fitbit product. Google has been busy around blood pressure lately, though. It ran a Fitbit Hypertension Lab study with Pixel Watch 3 owners last November, and Blood Pressure Trends is coming to the Pixel watches this fall as part of Health Guardian.

We also covered an earlier Fitbit patent that hinted at blood pressure checks from the wrist in April. Put the two finger filings next to that and Google is clearly working on blood pressure from several directions. Patents do not confirm a release though, so treat these as a look at what Google is exploring.

Source USPTO: September patent, August patent

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Its new Dream Recall feature uses real-time EEG data to work out when you are in REM sleep, then tries to wake you at the right moment while the dream is still fresh. The feature is now in beta as part of Smart Wakeup for Muse Premium subscribers using a Muse S or Muse S Athena.

The basic idea is pretty simple. Muse thinks remembering dreams has a lot to do with when you wake up, so instead of just sounding an alarm at a fixed time, the headband watches your brain activity overnight and looks for a better moment to pull you out of sleep.

It isn’t actually reading your dreams

It is worth being clear about what the headband is actually doing. Muse isn’t reading your dream, working out what you are dreaming about or recording anything happening inside your head.

Instead, its EEG sensors monitor brain activity and identify sleep stages in real time. When the system detects REM, Dream Recall can time the wake-up around that period rather than waiting until the dream has already started fading from memory.

Of course, dreaming and REM are not the same thing. Dreams can happen outside REM as well, but vivid dreaming is strongly associated with it, giving Muse a practical window to work with.

This is where EEG comes in

Muse has an advantage here over most smartwatches and smart rings. Those devices usually estimate sleep stages from signals such as movement and heart rate, while Muse measures electrical brain activity directly from the forehead.

That was one of the stronger parts of the Muse S Athena when I tested it. Its sleep tracking was particularly good at separating awake time from light sleep, an area where wrist-based trackers can sometimes struggle.

Muse has increasingly been using that EEG data while you are still asleep rather than simply handing you another chart the following morning. Deep Sleep Boost targets slow-wave sleep with timed audio, while Smart Wakeup looks for a lighter stage of sleep before sounding the alarm.

Dream Recall takes the same idea and points it at REM. There is also an Auto-Snooze function that reduces the sound as you begin to wake, with the idea of keeping you closer to that half-awake state where returning to the dream may be easier.

Muse is experimenting with sound cues too. Users can rehearse a cue while awake and then have it played during sleep, potentially making the sound recognisable inside a dream or helping with recall afterwards.

Wearables are starting to look at dreams

The idea of wearables moving into dreams isn’t unique to Muse. Earlier this year we uncovered an Oura patent describing dream detection and dream recall, including prompts and tools for recording what users remember after waking.

The big difference is that Muse has now moved beyond the design stage and put its version into a beta. Its EEG hardware also makes this a fairly natural extension of what the device is already measuring overnight.

Whether it actually leaves you remembering noticeably more dreams is the part that will need testing. Dream recall is subjective by nature, and waking people deliberately during REM also raises the obvious question of whether remembering more dreams is worth interrupting sleep for.

Those ready to dive in can pick up the Muse S Athena for $474.99 from the choosemuse.com website. To save 15%, use code “gadgetsandwearables” at check-out.

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