WHAT IS KNOWN?
- Organ conformal bioelectronics platform have enabled high-definition ventricular arrhythmia sensing, coupled with electrotherapy.
- 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?
- 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.
- 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.