融合音视频深度信息，非侵入式监测睡眠中的三大干扰事件。
A Sleep Monitoring System Based on Audio, Video and Depth Information
- 通过红外深度、彩色图像和麦克风阵列采集多模态数据。
- 能有效检测运动、灯光开关和噪音三类睡眠干扰事件。
- 适用于家庭环境，无需额外照明，适合睡眠研究与健康监测。
为定量评估睡眠障碍，本文提出一种基于事件的非侵入式监测系统。在家庭睡眠环境中，将睡眠干扰分为三类事件：运动事件、灯光开/关事件和噪声事件。系统采用配备红外深度传感器、RGB相机和四麦克风阵列的设备，在光照极弱环境下进行监测。针对深度信号建立背景模型以量化运动幅度；针对彩色图像建立另一背景模型以捕捉光照变化。通过事件检测算法从三类传感器的处理数据中识别事件发生。实验验证了系统在真实睡眠场景下的可靠性。
原文摘要 · Abstract (English)
For quantitative evaluation of sleep disturbances, a noninvasive monitoring system is developed by introducing an event-based method. We observe sleeping in home context and classify the sleep disturbances into three types of events: motion events, light-on/off events and noise events. A device with an infrared depth sensor, a RGB camera, and a four-microphone array is used in sleep monitoring in an environment with barely light sources. One background model is established in depth signals for measuring magnitude of movements. Because depth signals cannot observe lighting changes, another background model is established in color images for measuring magnitude of lighting effects. An event detection algorithm is used to detect occurrences of events from the processed data of the three types of sensors. The system was tested in sleep condition and the experiment result validates the system reliability.
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