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A physiological measures-based method for detecting inattention in drivers using machine learning approach

Paper ID Volume ID Publish Year Pages File Format Full-Text
5162 344 2015 8 PDF Available
Title
A physiological measures-based method for detecting inattention in drivers using machine learning approach
Abstract

BackgroundIn recent years, as a result of the usage of electronic gadgets in vehicles, driver inattention has become one of the major causes of road accidents that lead to severe physical injuries, deaths and significant economic losses. Statistics ensure the need of a reliable driver inattention detection system that can alert the driver before a mishap happens.MethodsIn this work, we aimed to develop a system that can detect inattention using electrocardiogram (ECG) and surface electromyogram (sEMG) signals. Cognitive and visual inattention was manipulated by asking the driver to respond to phone calls and short messaging services, respectively. A total of 15 male subjects participated in the data collection process. The subjects were asked to drive for two hours in a simulated environment at three different times of the day. ECG, sEMG and video were obtained throughout the experiment. The gathered physiological signals were preprocessed to remove noises and artefacts. The inattention features were extracted from the preprocessed signals using conventional statistical, higher-order statistical and higher-order spectral features. The features were classified using k-nearest neighbour analysis, linear discriminant analysis and quadratic discriminant analysis.ResultsThe bispectral features gave overall maximum accuracies of 98.12% and 90.97% for the ECG and EMG signals, respectively.ConclusionWe conclude that ECG and EMG signals can be explored further to develop a robust and reliable inattention detection system.

Keywords
ECG; EMG; Physiological measures; Driver inattention; Driver distraction
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A physiological measures-based method for detecting inattention in drivers using machine learning approach
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biocybernetics and Biomedical Engineering - Volume 35, Issue 3, 2015, Pages 198–205
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us