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Feature Extraction of Galvanic Skin Responses by Nonnegative Sparse Deconvolution
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Feature Extraction of Galvanic Skin Responses by Nonnegative Sparse Deconvolution (2017)Feature Extraction of Galvanic Skin Respo…cvxEDA: a Convex Optimization Approach to Electrodermal Activity Processing (2015)cvxEDA: a Convex Optimization…Automatic identification of artifacts in electrodermal activity data (2015)Automatic identification of a…Using electrodermal activity to recognize ease of engagement in children during social interactions (2014)Using electrodermal activity …Under pressure (2014)Under pressureStress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables (2006)Stress Detection in Computer …Detecting Stress During Real-World Driving Tasks Using Physiological Sensors (2005)Detecting Stress During Real-…Sensing walkability? Opportunities and limitations of electrodermal activity as an indicator of walkable urban environments (2024)Sensing walkability? Opportun…Deep Learning-Based Automated Emotion Recognition Using Multimodal Physiological Signals and Time-Frequency Methods (2024)Deep Learning-Based Automated…Toward Mental Effort Measurement Using Electrodermal Activity Features (2022)Toward Mental Effort Measurem…Sensitive Physiological Indices of Pain Based on Differential Characteristics of Electrodermal Activity (2021)Sensitive Physiological Indic…Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity (2021)Objective pain stimulation in…FLIRT: A feature generation toolkit for wearable data (2021)FLIRT: A feature generation t…Identification of Sympathetic Nervous System Activation From Skin Conductance: A Sparse Decomposition Approach With Physiological Priors (2020)Identification of Sympathetic…Affective Computing (1997)Pupil size variation as an indication of affective processing (2003)The Role of Nonlinear Dynamics in Affective Valence and Arousal Recognition (2011)Activity-Aware Mental Stress Detection Using Physiological Sensors (2012)Large-scale wearable data reveal digital phenotypes for daily-life stress detection (2018)Marital interaction: Physiological linkage and affective exchange. (1983)Parent–infant synchrony and the construction of shared timing; physiological precursors, developmental outcomes, and risk conditions (2007)Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications (2010)Deep Structures of Collaboration (2017)Measuring Engagement in Robot-Assisted Autism Therapy: A Cross-Cultural Study (2017)A Model-Free Affective Reinforcement Learning Approach to Personalization of an Autonomous Social Robot Companion for Early Literacy Education (2019)Inferring psychological significance from physiological signals. (1990)Discriminating Stress From Cognitive Load Using a Wearable EDA Device (2009)COGCAM (2016)Just Breathe (2018)Transformer-Based Self-Supervised Multimodal Representation Learning for Wearable Emotion Recognition (2023)Coefficient Alpha and the Internal Structure of Tests (1951)Toward machine emotional intelligence: analysis of affective physiological state (2001)A Multimodal Database for Affect Recognition and Implicit Tagging (2011)Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review (2020)Stress Recognition Using Wearable Sensors and Mobile Phones (2013)Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health (2017)The use of electrodermal activity (EDA) measurement to understand consumer emotions – A literature review and a call for action (2019)Wearable-Based Affect Recognition—A Review (2019)Detecting deception in pain expressions: the structure of genuine and deceptive facial displays (2002)Real-Time High-Level Acute Pain Detection Using a Smartphone and a Wrist-Worn Electrodermal Activity Sensor (2021)Automatic motion artifact detection in electrodermal activity data using machine learning (2022)Automated Pain Assessment using Electrodermal Activity Data and Machine Learning (2018)Design and Evaluation of Deep Learning Models for Continuous Acute Pain Detection Based on Phasic Electrodermal Activity (2023)Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection (2018)NeuroKit2: A Python toolbox for neurophysiological signal processing (2021)Optimization of Wearable Biosensor Data for Stress Classification Using Machine Learning and Explainable AI (2024)Speech Emotion Recognition Using Deep Learning Techniques: A Review (2019)Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study (2019)Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity (2019)Stress Detection with Machine Learning and Deep Learning using Multimodal Physiological Data (2020)
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References

  • 2005Detecting Stress During Real-World Driving Tasks Using Physiological Sensors2,205 cited
  • 2015cvxEDA: a Convex Optimization Approach to Electrodermal Activity Processing605 cited
  • 2006Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables290 cited
  • 2015Automatic identification of artifacts in electrodermal activity data279 cited
  • 2014Under pressure167 cited
  • 2014Using electrodermal activity to recognize ease of engagement in children during social interactions143 cited

Cited by

  • 2021Sensitive Physiological Indices of Pain Based on Differential Characteristics of Electrodermal Activity72 cited
  • 2021FLIRT: A feature generation toolkit for wearable data72 cited
  • 2021Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity51 cited
  • 2024Deep Learning-Based Automated Emotion Recognition Using Multimodal Physiological Signals and Time-Frequency Methods44 cited
  • 2020Identification of Sympathetic Nervous System Activation From Skin Conductance: A Sparse Decomposition Approach With Physiological Priors44 cited
  • 2022Toward Mental Effort Measurement Using Electrodermal Activity Features40 cited
  • 2024Sensing walkability? Opportunities and limitations of electrodermal activity as an indicator of walkable urban environments

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10 cited