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迈向使用听觉脑机接口实现用户友好的拼写:CharStreamer范式。

Towards user-friendly spelling with an auditory brain-computer interface: the CharStreamer paradigm.

作者信息

Höhne Johannes, Tangermann Michael

机构信息

Machine Learning Laboratory, Berlin Institute of Technology, Berlin, Germany; Neurotechnology group, Berlin Institute of Technology, Berlin, Germany.

BrainLinks-BrainTools Excellence Cluster, University of Freiburg, Freiburg, Germany.

出版信息

PLoS One. 2014 Jun 2;9(6):e98322. doi: 10.1371/journal.pone.0098322. eCollection 2014.

Abstract

Realizing the decoding of brain signals into control commands, brain-computer interfaces (BCI) aim to establish an alternative communication pathway for locked-in patients. In contrast to most visual BCI approaches which use event-related potentials (ERP) of the electroencephalogram, auditory BCI systems are challenged with ERP responses, which are less class-discriminant between attended and unattended stimuli. Furthermore, these auditory approaches have more complex interfaces which imposes a substantial workload on their users. Aiming for a maximally user-friendly spelling interface, this study introduces a novel auditory paradigm: "CharStreamer". The speller can be used with an instruction as simple as "please attend to what you want to spell". The stimuli of CharStreamer comprise 30 spoken sounds of letters and actions. As each of them is represented by the sound of itself and not by an artificial substitute, it can be selected in a one-step procedure. The mental mapping effort (sound stimuli to actions) is thus minimized. Usability is further accounted for by an alphabetical stimulus presentation: contrary to random presentation orders, the user can foresee the presentation time of the target letter sound. Healthy, normal hearing users (n = 10) of the CharStreamer paradigm displayed ERP responses that systematically differed between target and non-target sounds. Class-discriminant features, however, varied individually from the typical N1-P2 complex and P3 ERP components found in control conditions with random sequences. To fully exploit the sequential presentation structure of CharStreamer, novel data analysis approaches and classification methods were introduced. The results of online spelling tests showed that a competitive spelling speed can be achieved with CharStreamer. With respect to user rating, it clearly outperforms a control setup with random presentation sequences.

摘要

脑机接口(BCI)旨在实现将脑信号解码为控制命令,为闭锁综合征患者建立一条替代的通信途径。与大多数使用脑电图事件相关电位(ERP)的视觉BCI方法不同,听觉BCI系统面临着ERP响应的挑战,在被关注和未被关注的刺激之间,ERP响应的类别区分性较差。此外,这些听觉方法具有更复杂的界面,给用户带来了很大的工作量。为了实现最大限度用户友好的拼写界面,本研究引入了一种新颖的听觉范式:“CharStreamer”。该拼写器可以通过“请留意你想要拼写的内容”这样简单的指令来使用。CharStreamer的刺激包括30个字母和动作的语音。由于它们每个都由其自身的声音表示,而不是人工替代声音,因此可以通过一步操作进行选择。这样就将心理映射工作量(声音刺激到动作)降到了最低。按字母顺序呈现刺激进一步考虑到了可用性:与随机呈现顺序不同,用户可以预见目标字母声音的呈现时间。CharStreamer范式的健康、听力正常的用户(n = 10)显示出目标声音和非目标声音之间系统不同的ERP响应。然而,类别区分特征与随机序列控制条件下发现的典型N1 - P2复合波和P3 ERP成分相比,个体差异较大。为了充分利用CharStreamer的顺序呈现结构,引入了新的数据分析方法和分类方法。在线拼写测试结果表明,使用CharStreamer可以实现具有竞争力的拼写速度。在用户评分方面,它明显优于具有随机呈现序列的对照设置。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e25/4041754/c38d0506fce7/pone.0098322.g001.jpg

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