Bianchi Luigi, Quitadamo Lucia Rita, Garreffa Girolamo, Cardarilli Gian Carlo, Marciani Maria Grazia
Department of Neuroscience, "Tor Vergata" University, 00133 Rome, Italy.
IEEE Trans Neural Syst Rehabil Eng. 2007 Jun;15(2):207-16. doi: 10.1109/TNSRE.2007.897024.
The evaluation of the performances of brain-computer interface (BCI) systems could be difficult as a standard procedure does not exist. In fact, every research team creates its own experimental protocol (different input signals, different trial structure, different output devices, etc.) and this makes systems comparison difficult. Moreover, the great question is whether these experiments can be extrapolated to real world applications or not. To overcome some intrinsic limitations of the most used criteria a new efficiency indicator will be described and used. Its main advantages are that it can predict with a high accuracy the performances of a whole system, a fact that can be used to successfully improve its behavior. Finally, simulations were performed to illustrate that the best system is built by tuning the transducer (TR) and the control interface (CI), which are the two main components of a BCI system, so that the best TR and the best CI do not exist but just the best combination of them.
由于不存在标准程序，脑机接口（BCI）系统性能的评估可能会很困难。事实上，每个研究团队都创建自己的实验方案（不同的输入信号、不同的试验结构、不同的输出设备等），这使得系统比较变得困难。此外，最大的问题是这些实验能否外推到实际应用中。为了克服最常用标准的一些固有局限性，将描述并使用一种新的效率指标。其主要优点是它可以高精度地预测整个系统的性能，这一事实可用于成功改善其性能。最后，进行了模拟以说明最佳系统是通过调整换能器（TR）和控制接口（CI）构建的，它们是BCI系统的两个主要组件，因此不存在最佳的TR和最佳的CI，而只有它们的最佳组合。
