Research on Brainprint Recognition System Based on BP Neural Network

• Published in: Proceedings of ... IEEE International Conference on Cloud Computing and Big Data Analysis (Online) pp. 80 - 84
• Main Authors: Changrong, Yuan, Mingxu, Liang, Yongjin, Li
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24.04.2025
• Subjects: Accuracy; Accuracy Rate; Biological neural networks; Biometric identification; BP Neural Network; Brain modeling; Brainwave Recognition; Cloud computing; Identity Verification; Measurement; Nearest neighbor methods; Support vector machines; Testing; Training
• ISSN: 2832-3734
• DOI: 10.1109/ICCCBDA64898.2025.11030436

With the continuous development of biometric technology, brainwave recognition has gained significant attention as an emerging biometric identification technology. The brainwave recognition system based on the BP neural network is investigated in this research. A brainwave recognition model is established using the BP neural network algorithm, trained and tested on a dataset collected from 30 subjects at the Autonomous University of Querétaro in Mexico. The performance is compared with KNN, support vector machine, and random forest algorithms. The results indicate that the BP neural network achieves a superior accuracy rate of up to 92.97%, with the shortest testing time, effectively providing accurate and rapid identification of brainwave data. This research offers valuable guidance and reference for the research of brainwave-based identity recognition.