Chin Sam, Whitmore Nathan W, Perry Nathan, Paradiso Joe, Maes Pattie
Responsive Environments Group, MIT Media Lab, Cambridge, Massachusetts, United States of America.
Fluid Interfaces Group, MIT Media Lab, Cambridge, Massachusetts, United States of America.
PLoS One. 2025 Sep 11;20(9):e0329711. doi: 10.1371/journal.pone.0329711. eCollection 2025.
Sleep staging is a critical tool used in research and clinical settings to evaluate and diagnose sleep conditions; however, sleep staging is labor intensive and may be challenging for inexperienced practitioners. We explored whether adding an auditory representation (sonification) of the EEG to a standard visual representation could improve sleep staging performance or reduce workload. This is the first study to investigate the effects of sonification on sleep staging performance. We performed a within-subjects study in which 40 participants completed an online sleep staging task with and without sonified EEG. EEG was sonified by minimal transformation in which the raw EEG signal was played as an audio signal. Contrary to our hypothesis, we found adding sonification did not result in improvements in accuracy, speed, or workload for the entire subject group. However, when we stratified participants by sleep staging experience, we found sonification improved accuracy for the least experienced participants. These findings suggest EEG sonification may be useful as a tool to enable novice sleep stagers to reach acceptable performance levels faster.
睡眠分期是研究和临床环境中用于评估和诊断睡眠状况的关键工具；然而，睡眠分期需要耗费大量人力，对于缺乏经验的从业者来说可能具有挑战性。我们探讨了在标准视觉呈现的基础上增加脑电图的听觉呈现（声化）是否能提高睡眠分期的表现或减轻工作量。这是第一项研究声化对睡眠分期表现影响的研究。我们进行了一项受试者内研究，40名参与者在有和声化脑电图以及没有声化脑电图的情况下完成了一项在线睡眠分期任务。脑电图通过最小变换进行声化，即将原始脑电图信号作为音频信号播放。与我们的假设相反，我们发现添加声化并没有提高整个受试者组的准确性、速度或减轻工作量。然而，当我们根据睡眠分期经验对参与者进行分层时，我们发现声化提高了经验最少的参与者的准确性。这些发现表明，脑电图声化可能作为一种工具，使新手睡眠分期者能够更快地达到可接受的表现水平。
