Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:4097-4100. doi: 10.1109/EMBC48229.2022.9872003.
Detection of event-related potentials (ERPs) in brain-computer interfaces (BCIs) allow for communication by individuals with neuromuscular disorders. Enhancing BCI accuracy may be possible through the exploration of the optimal interstimulus interval (ISI). Our objective is to investigate the relationship between BCI accuracy and the optimal ISI value for an individual.
Using the previously developed classifier-based latency estimation (CBLE) [1], we investigated the relationship between the interstimulus interval (ISI) and P3 Speller BCI accuracy. Participants underwent two consecutive sessions in one day. The first session had a default ISI value of 120ms. An optimal ISI value calculated from the first session was used in the second.
Ten subjects participated in the study. Of the ten, half received an optimal ISI value of 120ms and half 160ms. Accuracy differences after implementing the adjusted ISI ranged from -26.1 percent to 4.35 percent. Suggestions for additional experimental design adjustments are highlighted under the discussion portion of this manuscript.
脑机接口（BCI）中的事件相关电位（ERP）检测可实现患有神经肌肉疾病的个体进行交流。通过探索最佳的刺激间隔（ISI），可能可以提高 BCI 的准确性。我们的目的是研究 BCI 准确性与个体最佳 ISI 值之间的关系。
使用先前开发的基于分类器的潜伏期估计（CBLE）[1]，我们研究了刺激间隔（ISI）与 P3 拼写器 BCI 准确性之间的关系。参与者在一天内进行了两次连续的测试。第一次测试的默认 ISI 值为 120ms。在第二次测试中，使用从第一次测试中计算出的最佳 ISI 值。
共有 10 名受试者参与了研究。其中一半接受的最佳 ISI 值为 120ms，另一半为 160ms。实施调整后的 ISI 后，准确性差异范围为-26.1%至 4.35%。在本手稿的讨论部分强调了其他实验设计调整的建议。
