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具有预测文本系统的二维听觉P300拼写器。

Two-dimensional auditory p300 speller with predictive text system.

作者信息

Hohne Johannes, Schreuder Martijn, Blankertz Benjamin, Tangermann Michael

机构信息

Machine Learning Department, Berlin Institute of Technology, Germany.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4185-8. doi: 10.1109/IEMBS.2010.5627379.

Abstract

P300-based Brain Computer Interfaces offer communication pathways which are independent of muscle activity. Mostly visual stimuli, e.g. blinking of different letters are used as a paradigm of interaction. Neural degenerative diseases like amyotrophic lateral sclerosis (ALS) also cause a decrease in sight, but the ability of hearing is usually unaffected. Therefore, the use of the auditory modality might be preferable. This work presents a multiclass BCI paradigm using two-dimensional auditory stimuli: cues are varying in pitch (high/medium/low) and location (left/middle/right). The resulting nine different classes are embedded in a predictive text system, enabling to spell a letter with a 9-class decision. Moreover, an unbalanced subtrial selection is investigated and compared to the well-established sequence-wise paradigm. Twelve healthy subjects participated in an online study to investigate these approaches.

摘要

基于P300的脑机接口提供了独立于肌肉活动的通信途径。大多使用视觉刺激,例如不同字母的闪烁作为交互范式。像肌萎缩侧索硬化症(ALS)这样的神经退行性疾病也会导致视力下降,但听力通常不受影响。因此,使用听觉模态可能更可取。这项工作提出了一种使用二维听觉刺激的多类脑机接口范式:线索在音高(高/中/低)和位置(左/中/右)上变化。由此产生的九个不同类别被嵌入到一个预测文本系统中,能够通过九类决策来拼写一个字母。此外,研究了不平衡的子试验选择并与成熟的序列范式进行比较。十二名健康受试者参与了一项在线研究来探究这些方法。

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