AI at the heart of new SFU gel-free ECG system for faster diagnoses

(Press-News.org) A new heart monitoring system combining 3D printing and artificial intelligence could transform the way doctors measure and diagnose patients' heart health.

Developed at SFU’s School of Mechatronic Systems Engineering, the system features reusable dry 3D-printed electrodes embedded in a soft chest belt – the folding origami-shaped design uses gentle suction to stick to the skin.

Carbon-based ink printed on the suction cup replaces electrolyte gel, conducting the heart’s electrical signals through to a wearable device with built-in AI software to pre-diagnose of up to 10 types of arrhythmias, or irregular heart rhythms. 

“Current ECG testing relies on single-use sticky patches and gel, which can dry out and fall off, and then the data must be manually interpreted by a doctor. This entire process takes more time and produces more medical waste than it needs to,” says Woo Soo Kim, professor at SFU’s School of Mechatronic Systems Engineering.

“Our dry electrodes are just as accurate as gel-based sensors, but they’re more comfortable for patients, easier to use, and they can be sanitized and reused to significantly reduce waste.”

Most importantly, the AI algorithm can help doctors make faster, more accurate diagnoses, with test results sent electronically to physicians for confirmation, he adds.

In their study published in Biosensors and Bioelectronics – led by SFU post-doctorate student Yiting Chen – Kim’s team tested the dry electrodes with frontline nurses from Vancouver General Hospital’s cardiac monitoring unit.

Nurses reported the dry electrodes and chest belt design could significantly improve patient comfort and compliance during long-term monitoring, which is currently done using bulky Holter monitors.

Rather than trying to re-stick patch sensors and mess around with electrolyte gel if an electrode falls off during the test, users simply press down on the origami-inspired electrode to recreate the seal.

According to the European Heart Rhythm Association, one in three people worldwide will develop a cardiac arrythmia, and the most common heart rhythm disorder – atrial fibrillation – is expected to increase globally by more than 60 per cent by 2050. 

Kim says this eco- and user-friendly tool presents a unique opportunity to improve personalized heart monitoring for long-term cardiac monitoring as well as high-demand healthcare settings, including emergency rooms, hospital wards, and senior care facilities.

It can also help people in rural and remote communities where access to diagnostic tools and physicians is limited.  

“It’s important that diagnostic tools are affordable and easy to access,” Kim says. “One of our goals is to see this tool being used in First Nations and remote communities, where people who need heart monitoring can take their own measurements, and our AI algorithm can analyze the data and provide an early assessment, which can then be shared with a doctor for a full diagnosis.”

Kim’s team is now focused on refining the AI’s pre-diagnostic algorithm, and shrinking the size of the 3D printed origami electrode down to one-third of its current height. 

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