Next Article in Journal
Packet-Forwarding Algorithm in DTN Based on the Pheromone of Destination Node
Previous Article in Journal
Smart Homes and Sensors for Surveillance and Preventive Education at Home: Example of Obesity
Article Menu

Export Article

Open AccessArticle
Information 2016, 7(3), 52; doi:10.3390/info7030052

Optimal Threshold Determination for Discriminating Driving Anger Intensity Based on EEG Wavelet Features and ROC Curve Analysis

1,2,3
,
1,2
,
3
and
1,2,*
1
Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan 430063, China
2
Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan 430063, China
3
Intelligent Human-Machine Systems Laboratory, Northeastern University, Boston, MA 02115, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 5 July 2016 / Revised: 14 August 2016 / Accepted: 17 August 2016 / Published: 26 August 2016
View Full-Text   |   Download PDF [3686 KB, uploaded 26 August 2016]   |  

Abstract

Driving anger, called “road rage”, has become increasingly common nowadays, affecting road safety. A few researches focused on how to identify driving anger, however, there is still a gap in driving anger grading, especially in real traffic environment, which is beneficial to take corresponding intervening measures according to different anger intensity. This study proposes a method for discriminating driving anger states with different intensity based on Electroencephalogram (EEG) spectral features. First, thirty drivers were recruited to conduct on-road experiments on a busy route in Wuhan, China where anger could be inducted by various road events, e.g., vehicles weaving/cutting in line, jaywalking/cyclist crossing, traffic congestion and waiting red light if they want to complete the experiments ahead of basic time for extra paid. Subsequently, significance analysis was used to select relative energy spectrum of β band (β%) and relative energy spectrum of θ band (θ%) for discriminating the different driving anger states. Finally, according to receiver operating characteristic (ROC) curve analysis, the optimal thresholds (best cut-off points) of β% and θ% for identifying none anger state (i.e., neutral) were determined to be 0.2183 ≤ θ% < 1, 0 < β% < 0.2586; low anger state is 0.1539 ≤ θ% < 0.2183, 0.2586 ≤ β% < 0.3269; moderate anger state is 0.1216 ≤ θ% < 0.1539, 0.3269 ≤ β% < 0.3674; high anger state is 0 < θ% < 0.1216, 0.3674 ≤ β% < 1. Moreover, the discrimination performances of verification indicate that, the overall accuracy (Acc) of the optimal thresholds of β% for discriminating the four driving anger states is 80.21%, while 75.20% for that of θ%. The results can provide theoretical foundation for developing driving anger detection or warning devices based on the relevant optimal thresholds. View Full-Text
Keywords: driving anger; road rage; electroencephalogram (EEG); receiver operating characteristic (ROC) curve; optimal threshold; wavelet transform; on-road experiments driving anger; road rage; electroencephalogram (EEG); receiver operating characteristic (ROC) curve; optimal threshold; wavelet transform; on-road experiments
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wan, P.; Wu, C.; Lin, Y.; Ma, X. Optimal Threshold Determination for Discriminating Driving Anger Intensity Based on EEG Wavelet Features and ROC Curve Analysis. Information 2016, 7, 52.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Information EISSN 2078-2489 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top