Research on data standardization methods of different EEG acquisition systems

Purpose This study addresses the data bias arising from different EEG devices in multicenter studies and proposes an EEG data standardization method based on amplitude-frequency response correction to mitigate the impact of device-specific performance variations on the acquired signals.Methods The effectiveness and applicability of the amplitude-frequency response correction algorithm were evaluated through simulation, the amplitude-frequency response data of 41 devices were collected and analyzed, and the effectiveness of the algorithm was verified by processing actual ERP data acquired using these devices.Results The amplitude-frequency response analysis reveals that, after eliminating interference from noise, bad lead, and other factors, responses across channels within the same device exhibit improved consistency. Accordingly, a correction template is generated for each device. Building on this template, the standardized amplitude-frequency response correction algorithm was enhanced. Experimental validation with real data confirmed that our method attenuates the influence of amplitude-frequency response discrepancies in the EEG acquisition system on the collected signals.Conclusion By systematically analyzing the differences in the amplitude-frequency responses of various EEG devices, we developed a set of standardization methods based on their performance parameters and provided a tool to support the standardization of experimental data across EEG acquisition systems in multi-center EEG studies.