Science Daily October 12, 2023
Although support vector machine algorithms for electrocardiogram classification show high classification accuracy, hardware implementations for edge applications are impractical due to the complexity and substantial power consumption needed for kernel optimization when using conventional CMOS circuits. A team of researchers in the US (Northwestern University, University of Southern California) has shown that reconfigurable mixed-kernel transistors based on dual-gated van der Waals heterojunctions could generate fully tunable individual and mixed Gaussian and sigmoid functions for analogue support vector machine kernel applications. The heterojunction-generated kernels can be used for arrhythmia detection from electrocardiogram signals with high classification accuracy compared with standard radial basis function kernels. Its reconfigurable nature allowed for personalized detection using Bayesian optimization. According to the researchers the device could generate the equivalent transfer function of a CMOS circuit comprising dozens of transistors and thus provide a low-power approach for support vector machine classification applications… read more. TECHNICAL ARTICLEÂ
MKH transistor schematic, structure, and performance. Credit: Nature Electronics, 2023