Kimura Riki, Nambu Isao, Fujitsuka Rui, Maruyama Yoshiko, Yano Shohei, Wada Yasuhiro
Graduate School of Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka, Nagaoka, Niigata, 940-2188, Japan.
Department of Production Systems Engineering, National Institute of Technology, Hakodate College, 14-1 Tokura, Hakodate, Hokkaido, 042-8501, Japan.
Heliyon. 2023 Dec 18;10(1):e23948. doi: 10.1016/j.heliyon.2023.e23948. eCollection 2024 Jan 15.
Volume control is necessary to adjust sound levels for a comfortable audio or video listening experience. This study aims to develop an automatic volume control system based on a brain-computer interface (BCI). We thus focused on a BCI using an auditory oddball paradigm, and conducted two types of experiments. In the first experiment, the participant was asked to pay attention to a target sound where the sound level was high (70 dB) compared with the other sounds (60 dB). The brain activity measured by electroencephalogram showed large positive activity (P300) for the target sound, and classification of the target and nontarget sounds achieved an accuracy of 0.90. The second experiment adopted a two-target paradigm where a low sound level (50 dB) was introduced as the second target sound. P300 was also observed in the second experiment, and a value of 0.76 was obtained for the binary classification of the target and nontarget sounds. Further, we found that better accuracy was observed in large sound levels compared to small ones. These results suggest the possibility of using BCI for automatic volume control; however, it is necessary to improve its accuracy for application in daily life.
音量控制对于调节声音水平以获得舒适的音频或视频收听体验是必要的。本研究旨在开发一种基于脑机接口(BCI)的自动音量控制系统。因此,我们专注于使用听觉Oddball范式的脑机接口,并进行了两种类型的实验。在第一个实验中,要求参与者关注与其他声音(60分贝)相比声音水平较高(70分贝)的目标声音。通过脑电图测量的大脑活动显示,目标声音出现了较大的正向活动(P300),目标声音和非目标声音的分类准确率达到了0.90。第二个实验采用了双目标范式,引入了低声音水平(50分贝)作为第二个目标声音。在第二个实验中也观察到了P300,目标声音和非目标声音的二元分类值为0.76。此外,我们发现与小声音水平相比,大声音水平下的准确率更高。这些结果表明了使用脑机接口进行自动音量控制的可能性;然而,有必要提高其在日常生活中的应用准确率。