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October 12, 2011IEEE Transactions on Intelligent Transportation Systems

Enhancement of the stress event detection model with driving event information increased accuracy from 82% (physiological features only) to 96%.

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Population

Drivers in real driving conditions

Comparison

Stress event detection model using physiological… vs Stress event detection based only on…

Design

Other

Authors

GRGeorge RigasNeurotechnics (United Kingdom)YGYorgos GoletsisUniversity of IoanninaDFDimitrios I. FotiadisCross-Cutting Cardiology

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Overview

May advance in-vehicle driver monitoring; leaves open prospective validation before safety-system deployment.

Structured PICO

P
Population
Drivers in real driving conditions
I
Intervention
Stress event detection model using physiological signals (electrocardiogram, electrodermal activity, respiration) and driving event information via a Bayesian network
C
Comparator
Stress event detection based only on physiological features
O
Outcome
Accuracy of stress event detection

Incorporating driving event information with physiological signals significantly improves the accuracy of real-time driver stress detection.

Cite This Study

Rigas et al. (2011) studied this question.

synapsesocial.com/papers/6a7155b55d37378ac1de7eddhttps://doi.org/10.1109/tits.2011.2168215
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Towards Driver's State Recognition on Real Driving Conditions2011 · 86 citations
  2. 2Designing an Intelligent System to Detect Stress Levels During Driving2021 · 4 citations
  3. 3Driving Stress Estimation in Physiological Signals Based on Hierarchical Clustering and Multi-View Intact Space Learning2021 · 15 citations
  4. 4Driver Stress Detection Based on Electrocardiogram Signals using Deep Learning Techniques2025
  5. 5Detection of driver stress in real-world driving environment using physiological signals2019 · 20 citations