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Posts tagged with "fitness"

Chance Miller on the Apple Watch Series 12 and Ultra 4→

Apple Watch reviews are out and Chance Miller at 9to5Mac has an excellent, in-depth look at both the Series 12 and Ultra 4. One of the things that Chance points out that might not be immediately obvious to many people is that the inclusion of an always-on chip as part of the S11 system on a chip allows Apple to fill meaningful gaps in both Watches’ data collection:

They will capture your heart rate every five seconds, regardless of whether you’re moving or stationary. Having such frequent and accurate heart rate readings unlocks new levels of data and insight.

When measuring your heart rate once every five minutes while stationary, previous Apple Watch models had an inherent blind spot. They either didn’t capture moments where your heart rate increased while not working out, or they captured one or two arbitrary readings somewhere in the middle of those moments.

That always-on component, combined with the Secure Exclave, is what Apple will also use to keep microphone data private and secure for features like Live Rewind and Siri Recap that are coming later this year.

It was these more frequent heart rate and HRV readings, along with the larger, more accurate sensor on the rear of the Apple Watches, that led me to order an Ultra 4. So I was also glad to see this observation from Chance after his first week with the new Watches:

In my one week with the Apple Watch Series 12 and Apple Watch Ultra 4, I’ve found that added data very insightful. I’m learning more about how little things I do throughout the day impact my heart rate. For example, I can visualize the impact of a late afternoon cup of coffee, or the impact of a stressful moment at work.

That’s the sort of feedback that you can act on and the kind of data that I expect developers will be able to use to make even more meaningful apps across the health and wellness spectrum.

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ChatGPT Is Surprisingly Thorough at Planning Running Routes→

Every now and then, I go looking for new running routes to mix things up, which was why I was intrigued by this post by Simon Willison, who gave ChatGPT Work his address and asked it to find 5K and 10K routes, using OpenStreetMap data:

It worked for 27 minutes and produced exactly what I’d asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here’s that 5K route:

Source: [simonwillison.com](https://simonwillison.net/2026/Sep/12/astra-running-routes/)

Source: simonwillison.com

I decided to give the same thing a try and was impressed by the results. ChatGPT spent a similar amount of time, poring over OpenStreetMap data, but it didn’t stop there. The model consulted my town’s website to account for road construction and the availability of sidewalks. Then, it visited the county’s website to review maps of greenways that aren’t part of the local road system. The final results were within 100m of exact 5K and 10K routes with notes on where to be careful to verify safe pathways and road crossings.

What I love about this sort of experiment is that it’s not something I’d ever have thought to ask ChatGPT myself. In hindsight, it’s obvious that all the data is there, ready to assemble. However, it just goes to show the many ways that I, and I’m sure many others, are still just scratching the surface of what LLMs make possible.

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watchOS 27: The MacStories Review

I haven’t been this excited about an Apple Watch in a long time. Last week, Apple introduced the Apple Watch Series 12 and Apple Watch Ultra 4, which will be available at the end of the week. The new Watches feature the S11 chip, which enables a bunch of new features, some of which won’t debut until later this year. At the same time, Apple is dropping support for more Watches than usual.

What we’re witnessing is a reboot of the Apple Watch and watchOS forced by advances in AI. The Apple Watch and its OS found their niche years ago, freeing us from pulling out our iPhones for notifications, tracking our health and fitness, and enabling the occasional Siri request. It was a good and comfortable spot for what by all accounts has been one of the most successful wearables to date, but watchOS also felt stuck in a rut.

Every year we got a few new workout types, a new watch face, and a few other features, but the OS didn’t advance much. What’s different this year is that watchOS 27 is breaking with slower hardware and looking forward to the substantially more powerful S11 chip, which will allow the Apple Watch to expand into all-new areas.

What this transition also means is that there is not just one set of features to track in watchOS 27 this year but three:

  • those that arrive today for anyone with a compatible Apple Watch,
  • those that arrive at the end of the week that are exclusive to the new Apple Watch Series 12 and Ultra 4, and
  • those that are coming later this year.

That makes this more than just a review. It’s also a preview of things to come and a roadmap for where the Apple Watch is heading.

There’s more than usual to cover this year, so let’s dive in and check it out.

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Pedometer++ 8: Glimmers of an Apple Wrist Renaissance

Today, when you mention David Smith’s name, most people probably think of Widgetsmith, his runaway success that caught fire on TikTok and is still going strong today. But for me, Pedometer++ is what comes to mind first. Still a couple of years away from releasing my own apps or writing at MacStories, I was fascinated by the dynamics that made the app a success when it debuted in 2013. Part of that success was how quickly David got it onto the App Store in the wake of the iPhone 5s and its M7 coprocessor that made step counting possible.

It didn’t hurt that Pedometer++’s initial release was also free (and the core features still are), but the app’s elegant, simple design played a big part, too. Pedometer++ appealed to a wide audience who appreciated its focus and frequent updates that systematically took it from basic step counting to badges, confetti, workouts, maps, and more. It’s a great example of a developer who jumped on a new hardware feature quickly with a focused initial release and then relentlessly iterated year after year without sacrificing what made that first version a favorite of so many people.

Today’s 8.0 release is focused first and foremost on the Apple Watch, which is the other aspect of so many of David’s apps that I appreciate. Few people know the ins and outs – and frustrations – of watchOS (née WatchKit) development like David does. But despite the platform’s rudimentary beginnings, David has stuck with it, making the best watch version of Pedometer++ that was possible with each turn of the SDK and, later, OS. That’s as true with version 8.0 of the app as it has ever been.

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Activas: Modern Design with a Sprinkling of AI

Activas is a new health and wellness tracker for the iPhone and iPad from developer Brian Hough, who built it from the ground up with Apple Intelligence and Liquid Glass in mind. The app serves as a dashboard that brings together information from the Health app in a colorful and easy-to-understand way, using progressive disclosure to avoid overwhelming users with data. It’s a fantastic example of modern design that marries form and function to elevate the user experience.

The app has just two tabs that adopt iOS 26’s Liquid Glass design without sacrificing legibility. The default view is the Dashboard, which can display your recent health and wellness metrics for the last 7, 15, or 30 days. At the top of the Dashboard is a Momentum Score that’s calculated based on a composite of step count, sleep, resting heart rate, and BMI targets, plus your calorie goal. Unlike many similar apps, Activas links to research supporting its targets, which I appreciate. The Momentum Score and a handful of additional stats can also be tracked using one of the app’s Home Screen widgets.

The Momentum Score is followed by an AI-generated insight about your metrics. Because I haven’t been tracking my calories or weight recently, the app suggested I should. That’s followed by overviews of Activity, Nutrition, Sleep, Vitals, and Body Measurement. Each of these sections appears as a SwiftUI-style card that includes graphs showing recent trends, an insight about your metrics, and a suggested question that you can ask the Activas AI with a tap. Sections can be turned on and off and reordered in the app’s settings, too.

The Dashboard’s design is superb. By collecting individual measurements in groups of related statistics and providing a takeaway about each section, the app allows users to get a quick, understandable overview of where they’re succeeding and what needs work.

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Finding the Best Sleep Tracker→

Earlier this year, Andrej Karpathy wrote an in-depth analysis of four sleep tracking methods that Federico recently recommended I read. I’m glad he did, Karpathy, an AI researcher who has worked at OpenAI and Tesla, took the kind of nerdy, data-driven approach that I love.

Over the course of two months, Karpathy plotted sleep tracking results from:

Karpathy got the best results from the Whoop band and Oura ring, but just as interesting were how the data correlated to how he felt after a good night’s sleep:

…my sleep scores correlate strongly with the quality of work I am able to do that day. When my score is low, I lack agency, I lack courage, I lack creativity, I’m simply tired. When my sleep score is high, I can power through anything. On my best days, I can sit down and work through 14 hours and barely notice the passage of time. It’s not subtle.

I recommend reading the entire post for all the details of how each tracking method compared on variety of metrics. I’ve long been intrigued by the Whoop band and Oura ring as a companion to the Apple Watch. There’s overlap between the devices, but Karpathy has planted a seed in my brain that may lead to my own multi-device experiments.

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watchOS 26: The MacStories Review

Last year was my first covering the watchOS beat with version 11. It turned out to be a trial by fire, with the annual software update for the world’s most popular smartwatch proving to be both sizable and significant.

While controversy reigned over iOS, iPadOS, and macOS regarding new Apple Intelligence features, watchOS took an exit off of that highway to a more peaceful, focused road that contained real, tangible updates. There were long-requested customizations to Activity Rings, as well as added power and functionality in the Smart Stack. Brand new features like Training Load and the Vitals app started to hint that Apple was maybe, finally, getting serious about, well, serious athletes.

If I’m being honest, I expected more of the same this year. The watchOS team seemed to be on a roll. Unfortunately, that hasn’t come to pass with watchOS 26, which – unlike watchOS 11 with Apple Intelligence – has been brought along for the ride with this year’s big controversy: Liquid Glass.

Can watchOS 26 handle this big UI overhaul and still deliver some tangible additions in this, the year of the Apple Watch’s tenth anniversary? Let’s take a look.

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Zenitizer: An Simple, Elegant Way to Practice and Track Meditation Sessions

Zenitizer 1.2, an iOS, iPadOS, and watchOS meditation app by Manuel Kehl, was released yesterday, adding iCloud sync support. The update means that progress toward your meditation goals and routines you create on any version of the app will sync across all devices for the first time. I recommended Zenitizer to Club MacStories readers not long ago when version 1.0 was released, but it’s such a well-designed and thought-out app, I wanted to go a little deeper today on everything it has to offer.

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Accounting for What the Apple Watch Ultra Can’t Track→

Every runner who has used a fitness tracker has a moment at some point that is similar to Victoria Song’s at this year’s New York City Half Marathon, where she was unable to beat her time from the year before:

I’d been running for nearly two hours in freezing temperatures, straight into the wind. The Apple Watch Ultra on my left wrist buzzed to tell me I’d just passed mile nine. On my right wrist, the Garmin Forerunner 265S said I’d only run 8.55 miles. A short-ish distance ahead, I could see the official mile nine marker. I had no idea which distance was “true.”

As someone who has had a borderline obsessive relationship with tracking personal fitness metrics at times, I can relate to wondering about the ‘true’ distance of a run. If you run the same route over and over, you’d think the distance would always be the same, but it’s not. As Song explains in her story for The Verge, the truth is much more complicated:

Altogether, the additional L5 signal is cross-referenced with data from Maps and Wi-Fi for what Mayor calls hyper-accurate GPS. It’s important to maintain a healthy skepticism, but it’s hard to argue that this method doesn’t deliver freakishly accurate location data. For instance, the Ultra (plus Series 8, SE, and any watch running watchOS 9) can automatically detect when you arrive at a running track. It also knows which lane you’re running in without calibration. If I hadn’t tried it out myself — multiple times, mind you — I’d be inclined to think it’s too good to be true.

Ultimately, Song attributes her slower 2023 time to the mental exhaustion of losing her mother to ALS in 2021. Her story is an excellent reminder that humans are complicated. We’re not robots, and although the data collected by our devices can help us become fitter, they can’t track everything, so it pays to listen to your body as well as your gadgets.

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