Feature Engineering and Machine Learning for Driver Sleepiness Detection

Falling asleep while operating a moving vehicle is a contributing factor to the statistics of road related accidents. It has been estimated that 20% of all accidents where a vehicle has been involv ...

[1]  G. Kecklund,et al.  Sleepiness in long distance truck driving: an ambulatory EEG study of night driving. , 1993, Ergonomics.

[2]  Nathaniel H. Hunt,et al.  The Appropriate Use of Approximate Entropy and Sample Entropy with Short Data Sets , 2012, Annals of Biomedical Engineering.

[3]  J. Bergeron,et al.  Fatigue and individual differences in monotonous simulated driving , 2003 .

[4]  Wendy Macdonald,et al.  Review of Relationships Between Steering Wheel Reversal Rate and Driving Task Demand , 1980 .

[5]  Göran Kecklund,et al.  Predicting road crashes from a mathematical model of alertness regulation--The Sleep/Wake Predictor. , 2008, Accident; analysis and prevention.

[6]  P. Laguna,et al.  Detection of driver's drowsiness by means of HRV analysis , 2011, 2011 Computing in Cardiology.

[7]  T. Higuchi Approach to an irregular time series on the basis of the fractal theory , 1988 .

[8]  T. Åkerstedt,et al.  Subjective and objective sleepiness in the active individual. , 1990, The International journal of neuroscience.

[9]  Michael Schrauf,et al.  EEG alpha spindle measures as indicators of driver fatigue under real traffic conditions , 2011, Clinical Neurophysiology.

[10]  A. Wayne Whitney,et al.  A Direct Method of Nonparametric Measurement Selection , 1971, IEEE Transactions on Computers.

[11]  D. Abásolo,et al.  Use of the Higuchi's fractal dimension for the analysis of MEG recordings from Alzheimer's disease patients. , 2009, Medical Engineering and Physics.

[12]  T. Åkerstedt,et al.  Use of subjective and physiological indicators of sleepiness to predict performance during a vigilance task. , 2007, Industrial health.

[13]  Madalena Costa,et al.  Multiscale entropy analysis of biological signals. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Peter Rossiter,et al.  Applying neural network analysis on heart rate variability data to assess driver fatigue , 2011, Expert Syst. Appl..

[15]  Andry Rakotonirainy,et al.  Driving performance impairments due to hypovigilance on monotonous roads. , 2011, Accident; analysis and prevention.

[16]  Joshua S. Martin,et al.  Removing the entropy from the definition of entropy: clarifying the relationship between evolution, entropy, and the second law of thermodynamics , 2013, Evolution: Education and Outreach.

[17]  Prabir Bhattacharya,et al.  A driver fatigue recognition model based on information fusion and dynamic Bayesian network , 2010, Inf. Sci..

[18]  Rongrong Fu,et al.  Automated Detection of Driver Fatigue Based on Entropy and Complexity Measures , 2014, IEEE Transactions on Intelligent Transportation Systems.

[19]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[20]  R. Uthayakumar,et al.  Application of fractal theory in analysis of human electroencephalographic signals , 2008, Comput. Biol. Medicine.

[21]  D. Dinges,et al.  The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. , 2003, Sleep.

[22]  C. Apte,et al.  Data mining with decision trees and decision rules , 1997, Future Gener. Comput. Syst..

[23]  Jirí Mekyska,et al.  Assessing progress of Parkinson's disease using acoustic analysis of phonation , 2015, 2015 4th International Work Conference on Bioinspired Intelligence (IWOBI).

[24]  Bruno Jammes,et al.  Automatic EOG analysis: A first step toward automatic drowsiness scoring during wake-sleep transitions , 2008 .

[25]  Josef Kittler,et al.  Floating search methods in feature selection , 1994, Pattern Recognit. Lett..

[26]  T. Åkerstedt,et al.  Reaction of sleepiness indicators to partial sleep deprivation, time of day and time on task in a driving simulator – the DROWSI project , 2009, Journal of sleep research.

[27]  Nadine Eberhardt,et al.  Bioelectrical Signal Processing In Cardiac And Neurological Applications , 2016 .

[28]  Ramesh Rajan,et al.  Combining complexity measures of EEG data: multiplying measures reveal previously hidden information , 2015, F1000Research.

[29]  E. F. Colecchia,et al.  Individual differences in subjective and objective alertness during sleep deprivation are stable and unrelated. , 2003, American journal of physiology. Regulatory, integrative and comparative physiology.

[30]  A. Wirz-Justice,et al.  Power density in theta/alpha frequencies of the waking EEG progressively increases during sustained wakefulness. , 1995, Sleep.

[31]  David Sandberg Detecting Driver Sleepiness , 2011 .

[32]  T. Åkerstedt,et al.  Having to stop driving at night because of dangerous sleepiness – awareness, physiology and behaviour , 2013, Journal of sleep research.

[33]  Arthur L. Samuel,et al.  Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..

[34]  Daniel Aeschbach,et al.  Dynamics of the human EEG during prolonged wakefulness: evidence for frequency-specific circadian and homeostatic influences , 1997, Neuroscience Letters.

[35]  Shuyan Hu,et al.  Driver drowsiness detection with eyelid related parameters by Support Vector Machine , 2009, Expert Syst. Appl..

[36]  Charles Lincoln Kenji Yamamura MACHINE LEARNING, INTERNET OF THINGS AND THE FUZZY FRONT END OF PRODUCT DEVELOPMENT , 2017 .

[37]  Arcady A. Putilov,et al.  The first and second principal components of the EEG spectrum as the correlates of sleepiness , 2012, Somnologie - Schlafforschung und Schlafmedizin.

[38]  Srdjan Kesic,et al.  Application of Higuchi's fractal dimension from basic to clinical neurophysiology: A review , 2016, Comput. Methods Programs Biomed..

[39]  Peter A. Flach,et al.  Machine Learning - The Art and Science of Algorithms that Make Sense of Data , 2012 .

[40]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[41]  S M Pincus,et al.  Approximate entropy as a measure of system complexity. , 1991, Proceedings of the National Academy of Sciences of the United States of America.