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Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal
6 references·2 citing·28 second hop
Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal (2020)Multi-level Stress Assessment Using Multi…Review on Psychological Stress Detection Using Biosignals (2019)Review on Psychological Stres…Multi-target affect detection in the wild (2019)Multi-target affect detection…Continuous stress detection using the sensors of commercial smartwatch (2019)Continuous stress detection u…An Explainable Deep Fusion Network for Affect Recognition Using Physiological Signals (2019)An Explainable Deep Fusion Ne…A Multichannel Convolutional Neural Network Architecture for the Detection of the State of Mind Using Physiological Signals from Wearable Devices (2019)A Multichannel Convolutional …Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection (2018)Introducing WESAD, a Multimod…Multilevel Stress Assessment From ECG in a Virtual Reality Environment Using Multimodal Fusion (2023)Multilevel Stress Assessment …Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures (2021)Real-Time Stress Level Feedba…Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)DEAP: A Database for Emotion Analysis ;Using Physiological Signals (2011)A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques (2021)A systematic review on affective computing: emotion models, databases, and recent advances (2022)Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations (2023)A circumplex model of affect. (1980)Stress, appraisal, and coping (1985)Emotion And Adaptation (1991)A Review on Mental Stress Assessment Methods Using EEG Signals (2021)A review on EEG-based multimodal learning for emotion recognition (2025)Manual for the State-Trait Anxiety Inventory (1970)Toward machine emotional intelligence: analysis of affective physiological state (2001)Comparison of Regression and Classification Models for User-Independent and Personal Stress Detection (2020)Detection of Artifacts in Ambulatory Electrodermal Activity Data (2020)Machine and Deep Learning Models for Stress Detection Using Multimodal Physiological Data (2025)Tightening the link between employee wellbeing at work and performance (2008)Continuous stress detection using a wrist device (2016)Stress Detection Through Wrist-Based Electrodermal Activity Monitoring and Machine Learning (2023)A Comparison of Personalized and Generalized Approaches to Emotion Recognition Using Consumer Wearable Devices: Machine Learning Study (2024)Detecting Stress During Real-World Driving Tasks Using Physiological Sensors (2005)Electrodermal Activity Based Pre-surgery Stress Detection Using a Wrist Wearable (2019)The Cook-Medley hostility scale: item content and ability to predict survival. (1989)EmotionMeter: A Multimodal Framework for Recognizing Human Emotions (2018)Self-Supervised ECG Representation Learning for Emotion Recognition (2020)A Transformer Architecture for Stress Detection from ECG (2021)Intelligent Stress Monitoring Assistant for First Responders (2021)Stress Detection Using Context-Aware Sensor Fusion From Wearable Devices (2023)
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References

  • 2018Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection1,356 cited
  • 2019Review on Psychological Stress Detection Using Biosignals763 cited
  • 2019Continuous stress detection using the sensors of commercial smartwatch107 cited
  • 2019An Explainable Deep Fusion Network for Affect Recognition Using Physiological Signals92 cited
  • 2019Multi-target affect detection in the wild56 cited
  • 2019A Multichannel Convolutional Neural Network Architecture for the Detection of the State of Mind Using Physiological Signals from Wearable Devices47 cited

Cited by

  • 2021Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures36 cited
  • 2023Multilevel Stress Assessment From ECG in a Virtual Reality Environment Using Multimodal Fusion33 cited

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