论文标题
对睡眠跟踪和改进设备的大规模研究，具有闭环和个性化的实时声学刺激
A Large-Scale Study of a Sleep Tracking and Improving Device with Closed-loop and Personalized Real-time Acoustic Stimulation
论文作者
论文摘要
从药物到高科技量身定制的解决方案的各种干预疗法都可以治疗困难，通常是由于现代生活中失眠而引起的。但是，由于缺乏精确的实时睡眠跟踪，对疗法的反馈，让人们在夜晚睡着的能力以及大规模的有效评估，因此目前的技术在很大程度上仍然不适合，无效和不可靠。在这里，我们介绍了一种称为Earable的新型睡眠援助系统，该系统可以不断地感知多个基于头部的生理信号，并同时使闭环听觉刺激能够及时吸收大脑活动，以促进有效的睡眠促进。我们以轻巧，舒适且用户友好的头带开发系统，并具有一系列算法和专用的自己设计的音频刺激。我们对377名受试者（241名女性，119名男性）的883次睡眠研究进行了多种方案，穿着金色标准设备（PSG），可耳朵或同时同时使用。 We demonstrate that our system achieves (1) a strong correlation (0.89 +/- 0.03) between the physiological signals acquired by Earable and those from the gold-standard PSG, (2) an 87.8 +/- 5.3% agreement on sleep scoring using our automatic real-time sleep staging algorithm with the consensus scored by three sleep technicians, and (3) a successful non-pharmacological stimulation alternative to effectively缩短睡眠持续时间降低24.1 +/- 0.1分钟。这些结果表明，Earable的功效超出了促进快速入睡，准确跟踪睡眠状态并获得实时闭环个性化神经调节的基于基于基于的神经调节的家庭睡眠护理的意图中的现有技术。
Various intervention therapies ranging from pharmaceutical to hi-tech tailored solutions have been available to treat difficulty in falling asleep commonly caused by insomnia in modern life. However, current techniques largely remain ill-suited, ineffective, and unreliable due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, an ability to keep people asleep during the night, and a large-scale effectiveness evaluation. Here, we introduce a novel sleep aid system, called Earable, that can continuously sense multiple head-based physiological signals and simultaneously enable closed-loop auditory stimulation to entrain brain activities in time for effective sleep promotion. We develop the system in a lightweight, comfortable, and user-friendly headband with a comprehensive set of algorithms and dedicated own-designed audio stimuli. We conducted multiple protocols from 883 sleep studies on 377 subjects (241 women, 119 men) wearing either a gold-standard device (PSG), Earable, or both concurrently. We demonstrate that our system achieves (1) a strong correlation (0.89 +/- 0.03) between the physiological signals acquired by Earable and those from the gold-standard PSG, (2) an 87.8 +/- 5.3% agreement on sleep scoring using our automatic real-time sleep staging algorithm with the consensus scored by three sleep technicians, and (3) a successful non-pharmacological stimulation alternative to effectively shorten the duration of sleep falling by 24.1 +/- 0.1 minutes. These results show that the efficacy of Earable exceeds existing techniques in intentions to promote fast falling asleep, track sleep state accurately, and achieve high social acceptance for real-time closed-loop personalized neuromodulation-based home sleep care.
