脑机接口的性能评估：教程
Performance measurement for brain-computer or brain-machine interfaces: a tutorial.
作者信息
Thompson David E, Quitadamo Lucia R, Mainardi Luca, Laghari Khalil Ur Rehman, Gao Shangkai, Kindermans Pieter-Jan, Simeral John D, Fazel-Rezai Reza, Matteucci Matteo, Falk Tiago H, Bianchi Luigi, Chestek Cynthia A, Huggins Jane E
机构信息
Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
出版信息
J Neural Eng. 2014 Jun;11(3):035001. doi: 10.1088/1741-2560/11/3/035001. Epub 2014 May 19.
OBJECTIVE
Brain-computer interfaces (BCIs) have the potential to be valuable clinical tools. However, the varied nature of BCIs, combined with the large number of laboratories participating in BCI research, makes uniform performance reporting difficult. To address this situation, we present a tutorial on performance measurement in BCI research.
APPROACH
A workshop on this topic was held at the 2013 International BCI Meeting at Asilomar Conference Center in Pacific Grove, California. This paper contains the consensus opinion of the workshop members, refined through discussion in the following months and the input of authors who were unable to attend the workshop.
MAIN RESULTS
Checklists for methods reporting were developed for both discrete and continuous BCIs. Relevant metrics are reviewed for different types of BCI research, with notes on their use to encourage uniform application between laboratories.
SIGNIFICANCE
Graduate students and other researchers new to BCI research may find this tutorial a helpful introduction to performance measurement in the field.
目的
脑机接口（BCI）有潜力成为有价值的临床工具。然而，BCI的多样性，再加上参与BCI研究的大量实验室，使得统一的性能报告变得困难。为解决这一情况，我们提供了一篇关于BCI研究中性能测量的教程。
方法
关于该主题的研讨会于2013年在加利福尼亚州太平洋格罗夫的阿西洛马会议中心举行的国际BCI会议上召开。本文包含了研讨会成员的共识意见，这些意见在接下来的几个月中通过讨论以及未能参加研讨会的作者的意见得以完善。
主要结果
针对离散和连续BCI都制定了方法报告清单。对不同类型的BCI研究的相关指标进行了综述，并对其使用进行了说明，以鼓励各实验室统一应用。
意义
刚接触BCI研究的研究生和其他研究人员可能会发现本教程对该领域的性能测量是一个有益的介绍。
Zotero 插件