使用智能手表驾驶时心跳和活动的变化作为睡意指标

S. Ríos-Aguilar, J. Merino, Andrés Millán Sánchez, Álvaro Sánchez Valdivieso
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引用次数: 22

摘要

困倦是造成事故的首要原因之一。估计10-30%的道路死亡与疲劳驾驶有关。为了降低开车时发生事故的风险,已经进行了大量的研究。这些研究中的许多都是基于对困倦/困倦的生物信号的检测。自主神经系统(ANS)的活动在不同的身体状态下呈现出变化,如压力或困倦。这种活动是通过ECG(脑电图)来测量的,在不同的研究中,它可以通过心跳的变化(hrv -心率变异性)来测量,以便分析它,然后检测驾驶员的嗜睡/困倦。与EEG传感器相比,HRV的主要优点是可以使用无创和不舒服的方式进行。新的可穿戴技术能够测量心跳,此外,使用其他传感器,如加速度计和陀螺仪,嵌入一个简单的时钟,使我们能够监控用户的身体活动。我们的主要目标是将脉搏测量与身体活动相结合,提前检测驾驶员的睡意,以防止疲劳引起的事故。
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Variation of the Heartbeat and Activity as an Indicator of Drowsiness at the Wheel Using a Smartwatch
Sleepiness is one of the first causal factors of accidents. An estimated 10-30% of road deaths are related to fatigue driving. A large number of research studies have been conducted to reduce the risk of accidents while driving. Many of these studies are based on the detection of biological signals by drowsiness/sleepiness. The activity of the autonomic nervous system (ANS) presented alterations during different physical states such as stress or sleepiness. This activity is measured by ECG (electroencephalogram) and, in different studies, it can be measured with the variation of the heart beat (HRV-Heart Rate Variability) in order to analyze it and then detect drowsiness/sleepiness in drivers. The main advantage is that HRV can be performed using non invasive and uncomfortable means compared to EEG sensors. New Wearables technologies are capable of measuring the heart beat and, further, using other sensors like Accelerometer and Gyroscope, embedded on a simple clock allow us to monitor the physical activity of the user. Our main goal is to use the pulsations measurements in conjunction with the physical activity for the detection of driver drowsiness/sleepiness in advance in order to prevent accidents derived from fatigue.
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