Bungie's Marathon arrives on March 5 How to claim Verizon's $20 outage credit Apple needs a better Siri, not an unproven wearable. So it's come to this: Apple is reportedly working on a wearable AI pin . According to, it is going to be a small device with multiple cameras, a speaker, microphones and wireless charging. It sounds like the perfect gadget to pair with the long-awaited AI-powered Siri update, which will also reportedly work as a chatbot . But while many Apple rumors conjure up an air of excitement, the notion of an Apple AI pin sounds downright baffling. Worse, it just seems desperate.

Apple's new Sleep Score feature gives Apple Watch users a single number rating for sleep quality, requiring watchOS 26 and iPhone with iOS 26 or later.

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The crown doubles as a way to scroll through the interface, which makes it easier to select items in various menus. There are also two pushers above and below the crown. The top opens a menu with the main capabilities of the watch, like fitness tracking, weather, calendar, and dialer. This button also acts as the select button, whereas the bottom pusher takes you to the previous menu.

Automatic sleep staging typically relies on gold-standard EEG setups, which are accurate but obtrusive and impractical for everyday use outside sleep laboratories. This limits applicability in real-world settings, such as home environments, where continuous, long-term monitoring is needed. Detecting sleep onset is particularly relevant, enabling consumer applications (e.g. automatically pausing media playback when the user falls asleep). Recent research has shown correlations between in-ear EEG and full-scalp EEG for various phenomena, suggesting wearable, in-ear devices could allow unobtrusive sleep monitoring. We investigated the feasibility of using single-channel in-ear electrophysiological (ExG) signals for automatic sleep staging in a wearable device by conducting a sleep study with 11 participants (mean age: 24), using a custom earpiece with a dry eartip electrode (Dätwyler SoftPulse) as a measurement electrode in one ear and a reference in the other. Ground truth sleep stages were obtained from an Apple Watch Ultra, validated for sleep staging. Our system achieved 90.5% accuracy for binary sleep detection (Awake vs. Asleep) and 65.1% accuracy for four-class staging (Awake, REM, Core, Deep) using leave-one-subject-out validation. These findings demonstrate the potential of in-ear electrodes as a low-effort, comfortable approach to sleep monitoring, with applications such as stopping podcasts when users fall asleep.

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High-quality, medically validated labels exist for clinical actigraphy data but not for ubiquitous consumer wearables like the Apple Watch. Manually labeling wearables data is expensive and doesn't scale. This paper offers a novel framework that transfers valuable labels from a source domain (e.g., actigraphy) to a target domain (e.g., Apple Watch) without requiring paired data. Instead of working with raw time-series signals, we project both domains into a shared latent embedding space using time-series foundation models (TSFMs) and develop a new framework to align the cross-device representations. Our method, Adversarial Alignment of TSFM Embeddings forces the distributions of source and target embeddings to align within this space, facilitating label transfer across device type.

Murdoch Children's Institute clinical science research director Dr. Vicki Anderson explains how the app will help parents and coaches rapidly assess injuries and determine how to treat them on'Varney & Co.' Falls are the number one cause of injury among adults 65 and older. But the truth is, your risk doesn't suddenly appear the day you turn 65. It increases gradually over time, especially if you're dealing with weak muscles, balance issues, side effects from medication, or even just forgetting a pill. Experts recommend that everyone get screened for fall risk at age 65. But you don't have to wait for a doctor's visit to take action.

An Apple Watch saved his life after it used SOS to call for help when he had a stroke in his driveway. What if your Apple Watch or iPhone could alert you to a pregnancy before a test does? A new Apple-funded study suggests that this is now within reach. Researchers used a mix of behavioral and biometric data to train an artificial intelligence model. The system correctly predicted pregnancy in 92% of cases.