A wireless neural recording microsystem with operator-based spike detection

Abstract

We introduce an innovative approach that incorporates operator-based spike detection in wireless microsystems for neural signal processing. Through comparative analyses between simple thresholding and operator-based detection conducted on pre-recorded spike detection experiments, our research emphasizes the superiority of the operator-based spike detection approach. The operator-based spike detection emerges as a promising technique for miniaturized wireless neural signal devices, primarily due to its proficient noise-handling capabilities paired with reduced power consumption. Furthermore, its adaptability across various experimental conditions amplifies its versatility. Empirical tests underscored its low power requisites and compactness, emphasizing practical utility of the detection scheme in the neural microsystems. Collectively, our results mark a significant progression in wireless cerebral signal recording methodologies, paving the way for optimized wireless brain-machine interface (BMI) systems.