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A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals

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References

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2021A comprehensive review and analysis of supervised-learning and soft computing techniques for stress diagnosis in humans126 cited
2020CNN and LSTM-Based Emotion Charting Using Physiological Signals125 cited
2020Multimodal Features for Detection of Driver Stress and Fatigue: Review

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2023Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals118 cited

2017Real-time mental stress detection based on smartwatch104 cited

2020Driver Fatigue Detection Systems Using Multi-Sensors, Smartphone, and Cloud-Based Computing Platforms: A Comparative Analysis92 cited

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2016Comparison of Machine Learning Techniques for Psychophysiological Stress Detection74 cited

2016Unobtrusive and Multimodal Wearable Sensing to Quantify Anxiety71 cited

2021Driving Stress Detection Using Multimodal Convolutional Neural Networks with Nonlinear Representation of Short-Term Physiological Signals63 cited