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Drowsiness Detection Using Photoplethysmography Signal

机译:使用光电容积描记仪信号进行嗜睡检测

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This study presents an innovative approach to detect drowsiness by using photoplethysmography signals which is easily acquirable with non-invasive techniques. Drowsiness detection based on biological signals is being employed in precautionary personal safety. Autonomous Nervous System (ANS) activity can be measured non-invasively from the Pulse Rate Variability (PRV) signal obtained from photoplethysmography signal (PPG), that comprises alterations during, relaxation, extreme fatigue and drowsiness episodes. Our hypothesis is that these variations manifest on PRV. In this work we develop an on-line detector of drowsiness based on PRV analysis. The databases have been collected with the aid of an external observer who decides upon each minute of the recordings as drowsy or awake, and constitutes our data base.
机译:这项研究提出了一种创新的方法,通过使用光体积描记术信号来检测睡意,这是非侵入性技术可以轻易获得的。为了预防人身安全,正在使用基于生物信号的嗜睡检测。可以通过从光体积描记术信号(PPG)获得的脉搏率变异性(PRV)信号以非侵入方式测量自主神经系统(ANS)的活动,该信号包括在放松,极度疲劳和嗜睡发作期间的变化。我们的假设是这些差异会在PRV上体现出来。在这项工作中,我们基于PRV分析开发了一种睡意在线检测器。这些数据库是在外部观察员的帮助下收集的,外部观察员决定记录的每一分钟是否昏昏欲睡,并构成了我们的数据库。

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