2023/01/23 by Ildar Rakhmatulin, Rakhmatulin, Ildar · 1 voice
Biochemistry, Genetics and Molecular Biology · Computer Science · Neuroscience · #Artificial Intelligence (cs.AI) #EEG and Brain-Computer Interfaces #FOS: Biological sciences #FOS: Computer and information sciences #Neurons and Cognition (q-bio.NC) #cs.AI #q-bio.NC
paper · pdf · doi:10.48550/arxiv.2301.11110
openalex publication_date 2023/01/23 · arxiv published 2023/01/23 · arxiv updated 2023/01/23 · openalex created_date 2023/01/28 · openalex updated_date 2026/07/28
Artificial intelligence has made significant advances in recent years and this has had an impact on the field of neuroscience. As a result, different architectures have been implemented to extract features from EEG signals in real time. However, the use of such architectures requires a lot of computing power. As a result, EEG devices typically act only as transmitters of EEG data, with the actual data processing taking place in a third-party device. That's expensive and not compact. In this paper, we present a shield that allows a single-board computer, the Jetson Nano from Nvidia, to be converted into a brain-computer interface and, most importantly, the Jetson Nano's capabilities allow machine learning tools to be used directly on the data collection device. Here we present the test results of the developed device. https://github.com/HackerBCI/EEG-with-JetsonNano