Smarter calculations could help health wearables use less energy

Smartwatches and other wearable devices can monitor our health and help detect irregular heart rhythms. But continuously analysing all that health data uses energy, and batteries only last so long. 

Researchers from the University of Twente and Vrije Universiteit Amsterdam have found a way to make these calculations much more energy efficient. In their experiments, their approach improved power efficiency by 64.9%. The research received an Outstanding Paper award at the Euromicro Conference on Digital System Design (DSD) in September 2026. 

Not every calculation needs to be exact 

A smartwatch that continuously monitors your heart must make many calculations. The more energy these calculations use, the sooner the battery runs out. So, the researchers asked a simple question: do all these calculations really need to be completely exact? 

They developed a system that analyses the electrical activity of the heart to detect irregular heart rhythms, also known as arrhythmias. It looks at individual heartbeats and uses an AI system trained to recognise different types of arrhythmias. 

The researchers then made some of the calculations less precise on purpose. This means the system works with less detailed numbers and needs less energy to perform the calculations. In their experiments, for example, they reduced the precision from 16 bits to 8 bits and replaced some exact calculations with approximate ones. They trained the AI system to deal with the small errors these approximations can cause.  

“If you train well, you can compensate for imprecision (to some extent) and gain significant energy efficiency,” says Ghayoor Gillani, assistant professor in the Computer Architecture for Embedded Systems group at the University of Twente. 

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