Research on EEG acquisition system of smart internet of things with enhanced Mamba

This paper explores an advanced system for the acquisition of brain electrical signals within the framework of intelligent systems. By integrating a sensor network, cloud platform, brain electrical signal acquisition system, data processing algorithms, and deep learning models, the system facilitates real-time monitoring, data transmission, storage, and intelligent recognition of brain electrical signals. In addition, we investigate the application of the Mamba deep learning model in the intelligent medical domain. To enhance the performance of the Mamba model, this paper proposes an Multi-branch Attention module and an multiscale Convolution module. On the UCI dataset, the Mamba model strengthened with these two modules significantly outperformed other traditional models, achieving an accuracy of 98.3%, with a model loss below 10e-7 and an AUC of 0.995. On the eegmmidb dataset, the enhanced new model improved the accuracy by 2.4% compared to the baseline model.