Electrocardiogram monitoring is essential for detecting heart rhythm disorders, yet current systems rely on disposable gel-based electrodes that can dry out, fall off, and generate significant medical waste. The process is often uncomfortable for patients and requires manual interpretation by clinicians, slowing diagnosis and limiting long-term monitoring. Now, a new wearable approach has demonstrated that heart signals can be captured comfortably, reused safely, and analyzed automatically to support faster and more accessible arrhythmia detection.

The system, developed by researchers at Simon Fraser University (Burnaby, BC, Canada), integrates reusable dry electrodes produced through 3D printing and embedded into a soft, adjustable chest belt intended for extended wear. Each electrode uses an origami-inspired suction structure that gently adheres to the skin without adhesives. Carbon-based conductive ink replaces traditional electrolyte gel, transmitting cardiac electrical signals to a wearable unit equipped with artificial intelligence (AI) software capable of pre-screening multiple types of heart rhythm abnormalities.

Evaluation of the technology showed that the dry electrodes performed with accuracy comparable to conventional gel-based ECG sensors while improving ease of use and patient comfort. In findings published in Biosensors and Bioelectronics, nurses reported that the belt-based system could improve compliance during long-term monitoring, which is typically performed using bulky Holter monitors. If an electrode loses contact, users can simply press the origami structure to restore suction rather than replacing patches or reapplying gel.

With arrhythmias expected to affect one in three people globally and atrial fibrillation rates projected to rise sharply, the system could support scalable and personalized heart monitoring. Its reusable design may reduce waste and costs while enabling deployment in emergency rooms, hospital wards, senior care facilities, and remote or underserved communities. The team plans to further refine the AI algorithm and reduce the physical size of the electrode to improve wearability. Future iterations are expected to enhance early detection and remote sharing of results with physicians for confirmation.

“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,” said Professor Woo Soo Kim, who led the research. “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.”

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