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Machine Learning Techniques for Arousal Classification from Electrodermal Activity: A Systematic Review
16 references·1 citing·45 second hop
Machine Learning Techniques for Arousal Classification from Electrodermal Activity: A Systematic Review (2022)Machine Learning Techniques for Arousal C…Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity (2019)Feature Extraction and Select…Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study (2019)Continuous Stress Detection U…Automatic driver stress level classification using multimodal deep learning (2019)Automatic driver stress level…Detection of Stress Levels from Biosignals Measured in Virtual Reality Environments Using a Kernel-Based Extreme Learning Machine (2017)Detection of Stress Levels fr…Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement (2015)Preferred reporting items for…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…The biovid heat pain database data for the advancement and systematic validation of an automated pain recognition system (2013)The biovid heat pain database…A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals (2013)A comparative evaluation of n…DEAP: A Database for Emotion Analysis ;Using Physiological Signals (2011)DEAP: A Database for Emotion …Call Center Stress Recognition with Person-Specific Models (2011)Call Center Stress Recognitio…Discriminating Stress From Cognitive Load Using a Wearable EDA Device (2009)Discriminating Stress From Co…Toward Emotion Recognition in Car-Racing Drivers: A Biosignal Processing Approach (2008)Toward Emotion Recognition in…Physiology-based affect recognition for computer-assisted intervention of children with Autism Spectrum Disorder (2008)Physiology-based affect recog…Eustress, distress, and interpretation in occupational stress (2003)Eustress, distress, and inter…A circumplex model of affect. (1980)A circumplex model of affect.Driver Drowsiness Detection: A Machine Learning Approach on Skin Conductance (2023)Driver Drowsiness Detection: …Emotion recognition based on physiological changes in music listening (2008)Painful data: The UNBC-McMaster shoulder pain expression archive database (2011)Automatic Pain Recognition from Video and Biomedical Signals (2014)Automatic Pain Assessment with Facial Activity Descriptors (2016)Automatic Recognition Methods Supporting Pain Assessment: A Survey (2019)Measuring emotion: The self-assessment manikin and the semantic differential (1994)Affective Computing (1997)A Multimodal Database for Affect Recognition and Implicit Tagging (2011)Investigating Critical Frequency Bands and Channels for EEG-Based Emotion Recognition with Deep Neural Networks (2015)AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild (2017)A theory of human motivation. (1943)Self-efficacy mechanism in human agency. 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(1979)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)Culture and the Self: Implications for Cognition, Emotion, and Motivation (1991)The Measurement of Observer Agreement for Categorical Data (1977)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. (2009)The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration (2009)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)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)Objective measures, sensors and computational techniques for stress recognition and classification: A survey (2012)Detecting Moments of Stress from Measurements of Wearable Physiological Sensors (2019)Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review (2021)Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review (2023)Stress Detection with Machine Learning and Deep Learning using Multimodal Physiological Data (2020)
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References

  • 2015Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement26,189 cited
  • 1980A circumplex model of affect.16,320 cited
  • 2011DEAP: A Database for Emotion Analysis ;Using Physiological Signals5,082 cited
  • 2009Discriminating Stress From Cognitive Load Using a Wearable EDA Device742 cited
  • 2015cvxEDA: a Convex Optimization Approach to Electrodermal Activity Processing605 cited
  • 2003Eustress, distress, and interpretation in occupational stress436 cited
  • 2019Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study351 cited
  • 2008Toward Emotion Recognition in Car-Racing Drivers: A Biosignal Processing Approach335 cited
  • 2013The biovid heat pain database data for the advancement and systematic validation of an automated pain recognition system288 cited
  • 2015Automatic identification of artifacts in electrodermal activity data279 cited
  • 2019Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity252 cited
  • 2011Call Center Stress Recognition with Person-Specific Models210 cited
  • 2013A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals194 cited
  • 2019Automatic driver stress level classification using multimodal deep learning

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189 cited
  • 2008Physiology-based affect recognition for computer-assisted intervention of children with Autism Spectrum Disorder163 cited
  • 2017Detection of Stress Levels from Biosignals Measured in Virtual Reality Environments Using a Kernel-Based Extreme Learning Machine162 cited
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    • 2023Driver Drowsiness Detection: A Machine Learning Approach on Skin Conductance34 cited