基于谱图分析的多普勒传感器瞬变持续时间估计

Kohei Yamamoto, Kentaroh Toyoda, T. Ohtsuki
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引用次数: 2

摘要

众所周知,眨眼的持续时间与睡意高度相关,眨眼的持续时间是一次眨眼的整个持续时间。因此,在驾驶员监控等各种应用中,在没有特殊可穿戴设备的情况下测量眨眼持续时间是很重要的。虽然多普勒传感器可能是实现这一目标的关键设备,但由于眼睑反射信号的信噪比较低,很难估计眨眼持续时间,目前还没有实现这种眨眼持续时间的估计方法。在本文中,我们提出了一种基于多普勒传感器的方法来估计与实际眨眼时间成比例的持续时间。该方法首先从接收到的信号中计算频谱图,然后从中提取眼睑闭合和打开的时间。更具体地说,瞬变是根据谱图上能量的重心来计算的。我们进行了实验五个主题展示该方法的估计精度。我们确认我们的方法取得了0.95的平均相关系数R,此外,平均RMSE(均方根误差)的46名女士。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Doppler Sensor-Based Blink Duration Estimation by Spectrogram Analysis
It is known that the blink duration is highly related to drowsiness, where the blink duration is the entire duration of one blink. Hence, it is important to measure the blink duration without any special wearable devices in various application, e.g., driver's monitoring. Although a Doppler sensor could be a key device to realize it, no such blink duration estimation method has been realized so far, since estimating the blink duration is difficult because of the low SNR (Signal to Noise Ratio) of the signal reflected from eyelids. In this paper, we propose a Doppler sensor-based method that estimates the duration, tblink, that is proportional to the actual blink duration. In the proposed method, a spectrogram is firstly calculated from a received signal, and then the timings when eyelids close and open are extracted from that. More specifically, tblink is calculated based on the center-of-gravity of the energy on a spectrogram. We conducted the experiments on five subjects to show the estimation accuracy of our proposed method. We confirmed that our method achieved the average correlation coefficient R of 0.95, furthermore, the average RMSE (Root Mean Square Error) of 46 ms.
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