WHAT IS KNOWN?

1. Organ conformal bioelectronics platform have enabled high-definition ventricular arrhythmia sensing, coupled with electrotherapy.
2. However, current conformal electronics platforms do not have the ability to perform real time computing to detect arrhythmia rotors and and subsequently deliver appropriate therapy.

WHAT THIS STUDY ADDS?

1. We propose the use of distributed computing algorithm based on cellular neural networks to provide high classification sensitivity, specificity, accuracy, and precision in detecting arrhythmia rotors and wavefronts.
2. The compact and efficient computing solution is readily mappable to a memristor based hardware circuitry and could enable a closed-loop solution for smart arrhythmia detection and real-time therapy.

LINK TO THE ARTICLE

Yang Z, Zhang L, Aras K, Efimov IR, Adam GC. Hardware-Mappable Cellular Neural Networks for Distributed Wavefront Detection in Next-Generation Cardiac Implants. Adv. Intell. Syst., 2022.