Objective. Real-time approaches for transcranial magnetic stimulation (TMS) based on a specific EEG phase are a promising avenue for more precise neuromodulation interventions. However, optimal approaches to reliably extract the EEG phase in a frequency band of interest to inform TMS are still to be identified. Here, we implement a new real-time phase detection method for closed-loop EEG-TMS for robust phase extraction. We compare this algorithm with state-of-the-art methods and evaluate its performance both in silico and experimentally. Approach. We propose a new robust algorithm (Educated Temporal Prediction) for delivering real-time EEG phase-specific stimulation based on short prerecorded EEG training data. This method estimates the interpeak period from a training period and applies a bias correction to predict future peaks. We compare the accuracy and computation speed of the ETP algorithm with two existing methods (Fourier based, Autoregressive Predi...

中文翻译：

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实时脑电相位特异性经颅磁刺激方法的实验评估。

目的。基于特定EEG期的经颅磁刺激（TMS）实时方法是进行更精确的神经调节干预的有希望的途径。然而，仍然需要确定在感兴趣的频带中可靠地提取EEG相位以通知TMS的最佳方法。在这里，我们为闭环EEG-TMS实现了一种新的实时相位检测方法，以实现可靠的相位提取。我们将该算法与最新方法进行了比较，并通过计算机和实验评估了其性能。方法。我们提出了一种新的鲁棒算法（Educated Temporal Prediction），用于基于简短的预先记录的EEG训练数据提供实时的EEG特定阶段刺激。此方法根据训练周期估算峰间周期，并应用偏差校正来预测未来的峰值。