IEEE Trans Neural Syst Rehabil Eng. 2018 Apr;26(4):874-881. doi: 10.1109/TNSRE.2018.2808425.
We conducted a study of a motor imagery brain-computer interface (BCI) using electroencephalography to continuously control a formant frequency speech synthesizer with instantaneous auditory and visual feedback. Over a three-session training period, sixteen participants learned to control the BCI for production of three vowel sounds (/ textipa i/ [heed], / textipa A/ [hot], and / textipa u/ [who'd]) and were split into three groups: those receiving unimodal auditory feedback of synthesized speech, those receiving unimodal visual feedback of formant frequencies, and those receiving multimodal, audio-visual (AV) feedback. Audio feedback was provided by a formant frequency artificial speech synthesizer, and visual feedback was given as a 2-D cursor on a graphical representation of the plane defined by the first two formant frequencies. We found that combined AV feedback led to the greatest performance in terms of percent accuracy, distance to target, and movement time to target compared with either unimodal feedback of auditory or visual information. These results indicate that performance is enhanced when multimodal feedback is meaningful for the BCI task goals, rather than as a generic biofeedback signal of BCI progress.
我们使用脑电图进行了一项运动想象脑-机接口 (BCI) 的研究,该接口使用即时听觉和视觉反馈来连续控制共振峰频率语音合成器。在三个会话的培训期间,十六名参与者学习控制 BCI 以产生三个元音 (/ textipa i/ [heed]、/ textipa A/ [hot] 和 / textipa u/ [who'd]),并分为三组:接收合成语音的单一听觉反馈、接收单一视觉反馈的共振峰频率和接收多模态、视听 (AV) 反馈的参与者。听觉反馈由共振峰频率人工语音合成器提供,视觉反馈是在第一个两个共振峰定义的平面的图形表示上的二维光标。我们发现,与单一听觉或视觉信息反馈相比,组合的 AV 反馈在准确性百分比、目标距离和到达目标的运动时间方面表现出最大的性能。这些结果表明,当多模态反馈对 BCI 任务目标有意义时,而不是作为 BCI 进展的通用生物反馈信号时,性能会得到提高。