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 […]