公开(公告)号：WO2017105976A1

公开(公告)日：2017-06-22

申请号：PCT/US2016/065484

申请日：2016-12-08

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： KANNAN, Aadharsh ,  RAMASWAMY, Govind ,  GUJJAR, Avinash ,  BHASKAR, Srinivas

IPC: A61B5/00 ,  A61B5/024 ,  A61B5/18 ,  B60K28/06 ,  G08B21/06 ,  B60W40/08

CPC classification number: A61B5/7282 ,  A61B5/0024 ,  A61B5/02405 ,  A61B5/16 ,  A61B5/18 ,  A61B5/6801 ,  A61B5/681 ,  A61B5/6898 ,  A61B5/7257 ,  A61B5/726 ,  A61B5/7264 ,  A61B5/7267 ,  A61B5/7405 ,  A61B5/742 ,  A61B5/746 ,  B60K28/06 ,  B60W2040/0827 ,  G08B21/06

Abstract: Drowsiness onset detection implementations predict when a person transitions from a state of wakefulness to a state of drowsiness based on heart rate information. Appropriate action is then taken to stimulate the person to a state of wakefulness or notify other people of their state (with respect to drowsiness/alertness). This generally involves capturing a person's heart rate information over time using one or more heart rate (HR) sensors and then computing a heart- rate variability (HRV) signal from the captured heart rate information. Using Discrete Fourier Transform and DiscreteWavelet Transform, the HRV signal is analyzed to extract features that are indicative of an individual's transition from a wakeful state to a drowsy state. The extracted features are input into an artificial neural net (ANN) that has been trained using the same features to identify when an individual makes the aforementioned transition to drowsiness. Whenever an onset of drowsiness is detected, a warning is initiated.

Abstract translation: 嗜睡发作检测实施方式基于心率信息来预测人从清醒状态转变为睡意状态的时间。 然后采取适当的行动刺激该人处于清醒状态或通知他人其状态（关于嗜睡/警觉）。 这通常涉及使用一个或多个心率（HR）传感器随时间捕捉人的心率信息，然后从捕捉的心率信息计算心率变异性（HRV）信号。 使用离散傅里叶变换和离散小波变换，分析HRV信号以提取指示个体从清醒状态转变为困倦状态的特征。 提取的特征被输入到人工神经网络（ANN）中，该人工神经网络已经使用相同的特征进行训练以识别个体何时使上述转变为困倦。 每当发现嗜睡，就会发出警告。