Journal ArticleDOI
Driver fatigue and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel
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TLDR
Real time driver health condition monitoring system with drowsiness alertness was proposed and the driver's health condition such as the normal, fatigued and drowsy states was analysed by evaluating the heart rate variability in the time and frequency domains.Abstract:
Real time driver health condition monitoring system with drowsiness alertness was proposed. A new embedded electrocardiogram (ECG) sensor with electrically conductive fabric electrodes on the steering wheel of a car was designed to monitor the driver's health condition. The ECG signals were measured at a sampling rate of 100 Hz from the driver's palms as they stay on a pair of conductive fabric electrodes located on the steering wheel. Practical tests were conducted using an embedded ECG sensor with a wireless sensor node, and their performance was assessed under non-stop 2 h driving test. The ECG signals were measured and transmitted wirelessly to a base station connected to a server PC in personal area network environment. The driver's health condition such as the normal, fatigued and drowsy states was analysed by evaluating the heart rate variability in the time and frequency domains.read more
Citations
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Journal ArticleDOI
Driver Fatigue Detection Systems: A Review
Gulbadan Sikander,Shahzad Anwar +1 more
TL;DR: This paper presents state-of-the-art review of recent advancement in the field of driver fatigue detection and various approaches have been compared for fatigue detection, and areas open for improvements are deduced.
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The state-of-the-art wireless body area sensor networks: A survey:
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ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges.
TL;DR: A generic architectural model for ECG monitoring systems is proposed, an extensive analysis of ECG Monitoring systems’ value chain is conducted, and a thorough review of the relevant literature, classified against the experts’ taxonomy, is presented, highlighting challenges and current trends.
Journal ArticleDOI
Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions.
TL;DR: A drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles collected from sensors mounted on the steering lever, confirms that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue.
Journal ArticleDOI
Wearable Noncontact Armband for Mobile ECG Monitoring System
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References
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Journal ArticleDOI
Heart rate variability. Standards of measurement, physiological interpretation, and clinical use
Marek Malik,J. Thomas Bigger,A. John Camm,Robert E. Kleiger,Alberto Malliani,Arthur J. Moss,Peter J. Schwartz +6 more
Journal ArticleDOI
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Kim Fox,Jeffrey S. Borer,A. John Camm,Nicolas Danchin,Roberto Ferrari,José Luis López Sendón,Philippe Gabriel Steg,Jean-Claude Tardif,Luigi Tavazzi,Michal Tendera +9 more
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Journal ArticleDOI
Power spectrum analysis of heart rate variability: a tool to explore neural regulatory mechanisms.
TL;DR: Important new information has been generated by coupling the analysis of heart rate variability (HRV) to the concept of sympatho-vagal balance, which explains part of the variability of RR interval.
Journal ArticleDOI
EEG-based drowsiness estimation for safety driving using independent component analysis
TL;DR: In this paper, the authors developed a drowsiness-estimation system based on electroencephalogram (EEG) by combining independent component analysis (ICA), power-spectrum analysis, correlation evaluations, and linear regression model to estimate a driver's cognitive state when he/she drives a car in a virtual reality (VR)-based dynamic simulator.
Journal ArticleDOI
Electroencephalographic study of drowsiness in simulated driving with sleep deprivation
TL;DR: This study deals with time variant EEG change of sleep-deprived drivers—an important aspect of driver drowsiness analysis and can be used to estimate overall alertness level of drivers.