Wednesday, January 21, 2026
Patents

Apple Watches may one day be able to determine your chronological age and biological age

This graphic illustrates an evaluation of the relative risk of various diseases to affect age gap.

Future Apple Watches may be able to determine how old you are compared to how old you are, health-wise. Apple has filed for a patent for “Biological Age Determination Using a Wearable Device.”

About the patent filing

Actually, it’s a health care feature. The patent filing involves an Apple Watch being able to determine the various physiological parameters of a user. They can be measured and analyzed to estimate other physiological measures indicative of the user’s physiological state.

According to the patent filing, aspects of the subject technology utilize signals from a wearable device to predict a biological age of a user. A person’s biological age can be understood to be the effective age of the person’s physiology as impacted by health considerations which may positively or negatively impact the person’s health. 

For example, if a person had no health considerations, then their biological age would approximately match their chronological age (e.g., their age measured from their date of birth). If a person has negative health issues, their biological age may appear to be older than their chronological age, whereas if a person is healthier than would be typical, their biological age may appear to be younger than their chronological age. 

For example, a person with health issues may be physiologically older than their chronological age, that is, produce physiological markers which can be measured by sensors which have characteristics of a person older than their chronological age. If the Apple Watch sensors show a big gap between a person’s “real” age compared to their biological age, it could lead to the discovery and treatment of health issues. 

Summary of the patent filing

Here’s Apple’s abstract of the patent filing: “Aspects of the subject technology provide for training a machine learning model based on data from a healthy cohort of study participants. The machine learning model can be used to predict an age of a user based on physiological sensor data and determine a biological age of a user. 

“An age gap can be determined between the user’s chronological age and biological age and a notification or recommendation made to the user based on the age gap. An age gap rate of change can be made across multiple age gap determinations.

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Dennis Sellers
the authorDennis Sellers
Dennis Sellers is the editor/publisher of Apple World Today. He’s been an “Apple journalist” since 1995 (starting with the first big Apple news site, MacCentral). He loves to read, run, play sports, and watch movies.

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