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Recognition of Blinks Activity Patterns during Stress Conditions Using CNN and Markovian Analysis
8 references·1 citing·37 second hop
Recognition of Blinks Activity Patterns during Stress Conditions Using CNN and Markovian Analysis (2021)Recognition of Blinks Activity Patterns d…Respiratory signal and human stress: non-contact detection of stress with a low-cost depth sensing camera (2020)Respiratory signal and human …Review on Psychological Stress Detection Using Biosignals (2019)Review on Psychological Stres…Automatic driver stress level classification using multimodal deep learning (2019)Automatic driver stress level…A novel multi-kernel 1D convolutional neural network for stress recognition from ECG (2019)A novel multi-kernel 1D convo…A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor (2017)A Study of Deep CNN-Based Cla…Stress and anxiety detection using facial cues from videos (2016)Stress and anxiety detection …Experimental evaluation of eye-blink parameters as a drowsiness measure (2003)Experimental evaluation of ey…International Affective Picture System (IAPS) : Technical Manual and Affective Ratings (1995)International Affective Pictu…Detection of mental stress using novel spatio-temporal distribution of brain activations (2023)Detection of mental stress us…Quantification of Sleepiness: A New Approach (1973)A New Method for Measuring Daytime Sleepiness: The Epworth Sleepiness Scale (1991)Vehicle accidents related to sleep: a review. (1999)Subjective sleepiness, simulated driving performance and blink duration: examining individual differences (2006)Regional brain wave activity changes associated with fatigue (2012)Detection and prediction of driver drowsiness using artificial neural network models (2017)The expression of the emotions in man and animals. (1872)Stress, appraisal, and coping (1985)Stress: Appraisal and Coping (2013)The association between smartphone use, stress, and anxiety: A meta‐analytic review (2018)A survey of machine learning techniques in physiology based mental stress detection systems (2019)Stress Detection with Machine Learning and Deep Learning using Multimodal Physiological Data (2020)Vision-based method for detecting driver drowsiness and distraction in driver monitoring system (2011)Driver’s eye blinking detection using novel color and texture segmentation algorithms (2012)A review of driver fatigue detection and its advances on the use of RGB-D camera and deep learning (2022)Detecting Stress During Real-World Driving Tasks Using Physiological Sensors (2005)Toward Emotion Recognition in Car-Racing Drivers: A Biosignal Processing Approach (2008)Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection (2018)Audio based depression detection using Convolutional Autoencoder (2021)Driver stress detection via multimodal fusion using attention-based CNN-LSTM (2021)Human-Machine Shared Driving: Challenges and Future Directions (2022)A circumplex model of affect. (1980)Emotion And Adaptation (1991)A Review on Mental Stress Assessment Methods Using EEG Signals (2021)A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques (2021)A review on EEG-based multimodal learning for emotion recognition (2025)Discriminating Stress From Cognitive Load Using a Wearable EDA Device (2009)Stress Recognition Using Wearable Sensors and Mobile Phones (2013)Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures (2021)Emotion recognition system using short-term monitoring of physiological signals (2004)End-to-End Multimodal Emotion Recognition Using Deep Neural Networks (2017)The Stroop Color and Word Test (2017)The social readjustment rating scale (1967)A Global Measure of Perceived Stress (1983)A cognitive-motivational analysis of anxiety (1998)Attentional Biases for Negative Interpersonal Stimuli in Clinical Depression. (2004)Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review (2020)
this work references cited by second hop

References

  • 1995International Affective Picture System (IAPS) : Technical Manual and Affective Ratings2,892 cited
  • 2019Review on Psychological Stress Detection Using Biosignals763 cited
  • 2003Experimental evaluation of eye-blink parameters as a drowsiness measure388 cited
  • 2016Stress and anxiety detection using facial cues from videos343 cited
  • 2019Automatic driver stress level classification using multimodal deep learning189 cited
  • 2017A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor89 cited
  • 2020Respiratory signal and human stress: non-contact detection of stress with a low-cost depth sensing camera37 cited
  • 2019A novel multi-kernel 1D convolutional neural network for stress recognition from ECG36 cited

Cited by

  • 2023Detection of mental stress using novel spatio-temporal distribution of brain activations32 cited

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