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• W3159796803 abstract "We propose a novel method to estimate the instantaneous oscillatory phase to implement a real-time system for closed-loop sensory stimulation in electroencephalography (EEG) experiments. The method uses Kalman filter-based prediction to estimate current and future EEG signals. We tested the performance of our method in a real-time situation. We demonstrate that the performance of our method shows higher accuracy in predicting the EEG phase than the conventional autoregressive model-based method. A Kalman filter allows us to easily estimate the instantaneous phase of EEG oscillations based on the automatically estimated autoregressive model implemented in a real-time signal processing machine. The proposed method has a potential for versatile applications targeting the modulation of EEG phase dynamics and the plasticity of brain networks in relation to perceptual or cognitive functions." @default.
• W3159796803 created "2021-05-10" @default.
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• W3159796803 date "2021-04-26" @default.
• W3159796803 modified "2023-10-16" @default.
• W3159796803 title "A closed-loop stimulation approach with real-time estimation of the instantaneous phase of neural oscillations by a Kalman filter" @default.
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• W3159796803 doi "https://doi.org/10.1101/2021.04.25.441309" @default.
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