Hohne Johannes, Schreuder Martijn, Blankertz Benjamin, Tangermann Michael
Machine Learning Department, Berlin Institute of Technology, Germany.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4185-8. doi: 10.1109/IEMBS.2010.5627379.
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.
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。
