NapWell: An EOG-based Sleep Assistant Exploring the Effects of Virtual Reality on Sleep Onset
NapWell: An EOG-based Sleep Assistant Exploring the Effects of Virtual Reality on Sleep Onset
复制标题
NapWell：基于 EOG 的睡眠助手，探索虚拟现实对睡眠开始的影响
DOI：
10.1007/s10055-021-00571-w
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发表时间：
2021
期刊：
影响因子：
4.2
通讯作者：
Kunze Kai
中科院分区：
文献类型：
--
作者：
Pai Yun Suen;Bait Marsel L.;Lee Juyoung;Xu Jingjing;Peiris Roshan L;Woo Woontack;Billinghurst Mark;Kunze Kai
我们目前NapWell，睡眠助理使用虚拟现实（VR），以减少睡眠开始延迟提供一个现实的图像分心之前，睡眠开始。我们提出的原型是使用商业硬件构建的，成本相对较低，使其可用于未来的工作，并为更低成本的EOG-VR睡眠辅助设备铺平了道路。我们通过比较不同的睡眠条件进行了用户研究（）;无设备，睡眠面罩，研究室的VR环境和参与者首选的VR环境。在此期间，我们记录了眼电图（EOG）信号和睡眠开始时间使用手指敲击任务（FTT）。我们发现VR能够显着减少睡眠起始潜伏期。我们还开发了一种基于EOG信号的机器学习模型，可以预测睡眠开始，交叉验证的准确率为70.03%。本研究证明了VR作为一种减少睡眠开始潜伏期的工具的可行性，以及使用嵌入式EOG传感器与VR进行自动睡眠检测的可行性。
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 () 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.