We present NapWell, a Sleep Assistant using virtual reality (VR) to decrease sleep onset latency by providing a realistic imagery distraction prior to sleep onset. Our proposed prototype was built using commercial hardware and with relatively low cost, making it replicable for future works as well as paving the way for more low cost EOG-VR devices for sleep assistance. We conducted a user study (\(n= 20\)) by comparing different sleep conditions; no devices, sleeping mask, VR environment of the study room and preferred VR environment by the participant. During this period, we recorded the electrooculography (EOG) signal and sleep onset time using a finger tapping task (FTT). We found that VR was able to significantly decrease sleep onset latency. We also developed a machine learning model based on EOG signals that can predict sleep onset with a cross-validated accuracy of 70.03%. The presented study demonstrates the feasibility of VR to be used as a tool to decrease sleep onset latency, as well as the use of embedded EOG sensors with VR for automatic sleep detection.

我们展示了 NapWell，这是一种使用虚拟现实 (VR) 的睡眠助手，通过在睡眠开始前提供逼真的图像分散注意力来减少睡眠开始延迟。我们提出的原型是使用商业硬件构建的，成本相对较低，使其可复制用于未来的工作，并为更低成本的 EOG-VR 设备用于睡眠辅助铺平了道路。我们进行了一项用户研究 ( \(n= 20\)) 通过比较不同的睡眠条件；没有设备、睡眠面罩、自习室的 VR 环境和参与者首选的 VR 环境。在此期间，我们使用手指敲击任务 (FTT) 记录了眼电图 (EOG) 信号和睡眠开始时间。我们发现 VR 能够显着降低睡眠延迟。我们还开发了一种基于 EOG 信号的机器学习模型，该模型可以以 70.03% 的交叉验证准确度预测睡眠开始。所提出的研究证明了 VR 可用作减少睡眠延迟的工具，以及使用具有 VR 的嵌入式 EOG 传感器进行自动睡眠检测的可行性。