Health-app maker Cardiogram on Wednesday launched a feature that lets users monitor a loved one’s wearable data across Android and iOS devices.
Cardiogram breaks down heart rate data from the Apple Watch, Google’s Wear OS devices, and Garmin watches to help users understand their health, sleep patterns, stress levels and fitness. The app’s new cross-platform feature, called Family Mode, lets users remotely monitor a loved one’s data such as heart rate, step count, sleep and workouts.
A link lets people view the information within the Cardiogram app, regardless of whether both people have an Android, iOS or other compatible device. If a person uses an Apple Watch and a loved one has an Android phone, for example, they’ll still be able to share data. A family member can also switch into a relative’s profile and act on his or her behalf to enter the right insurance information, for instance.
Family Mode is available in Cardiogram’s new premium tab, which costs $15 a month after a one month free trial. Users who pay for six months or a year in advance get a discount. Compatible wearables include all versions of the Apple Watch, Garmin devices and WearOS gadgets.
Cardiogram Premium also includes a Share with Doctor feature, which lets users get a PDF of their data to share with a physician. The Cardiogram app itself is free to download on the App Store and Google Play.
Wearable devices arethat can potentially . People aged 55 and older are the fastest-growing group of wearable users in the US, according to eMarketer. In addition, the average Cardiogram user is 41 years old and more likely than the general population to manage a chronic condition like sleep apnea, diabetes, hypertension or atrial fibrillation, according to Cardiogram.
Cross-platform support could prove to be helpful given that the top five wearable companies combined — Xiaomi, Apple, Fitbit, Huawei and Samsung — make up just half of wearable shipments, according to IDC.
Cardiogram’s algorithms have accurately detected health conditions such as sleep apnea, hypertension,, and using a heart rate sensor and a deep neural network called DeepHeart.
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