脑机接口翻译算法的参数是否应该持续调整？
Should the parameters of a BCI translation algorithm be continually adapted?
机构信息
Laboratory of Neural Injury and Repair, Wadsworth Center, New York State Department of Health, Albany, NY 12201-0509, United States.
出版信息
J Neurosci Methods. 2011 Jul 15;199(1):103-7. doi: 10.1016/j.jneumeth.2011.04.037. Epub 2011 May 6.
Abstract
People with or without motor disabilities can learn to control sensorimotor rhythms (SMRs) recorded from the scalp to move a computer cursor in one or more dimensions or can use the P300 event-related potential as a control signal to make discrete selections. Data collected from individuals using an SMR-based or P300-based BCI were evaluated offline to estimate the impact on performance of continually adapting the parameters of the translation algorithm during BCI operation. The performance of the SMR-based BCI was enhanced by adaptive updating of the feature weights or adaptive normalization of the features. In contrast, P300 performance did not benefit from either of these procedures.
摘要
有运动障碍或无运动障碍的人都可以学习控制从头皮记录的感觉运动节律 (SMR)，以在一个或多个维度上移动计算机光标，或者可以使用 P300 事件相关电位作为控制信号进行离散选择。从使用基于 SMR 或 P300 的脑机接口的个体中收集的数据在离线时进行评估，以估计在脑机接口操作过程中不断调整翻译算法参数对性能的影响。通过自适应更新特征权重或自适应归一化特征，基于 SMR 的脑机接口的性能得到了增强。相比之下，这两种方法都不能提高 P300 的性能。
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