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Applications of artificial intelligence−machine learning for detection of stress: a critical overview

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References

2001Toward machine emotional intelligence: analysis of affective physiological state2,334 cited
2005Detecting Stress During Real-World Driving Tasks Using Physiological Sensors2,205 cited
2018Statistical and Machine Learning forecasting methods: Concerns and ways forward1,515 cited
2018Trajectories of resilience and dysfunction following potential trauma: A review and statistical evaluation877 cited
2013636,120 Ways to Have Posttraumatic Stress Disorder776 cited
2009Looking for resilience: Understanding the longitudinal trajectories of responses to stress615 cited
2017Instagram photos reveal predictive markers of depression519 cited
2019Stress detection in daily life scenarios using smart phones and wearable sensors: A survey479 cited
2015Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review476 cited
2014Predicting the present with Bayesian structural time series394 cited
2019Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study351 cited
2020Predicting Perceived Stress Related to the Covid-19 Outbreak through Stable Psychological Traits and Machine Learning Models291 cited
2006Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables290 cited

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2017

Machine Learning Framework for the Detection of Mental Stress at Multiple Levels

274 cited

2014How well can post-traumatic stress disorder be predicted from pre-trauma risk factors? An exploratory study in the WHO World Mental Health Surveys255 cited

2017Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health251 cited

Cited by

2025Machine and Deep Learning Models for Stress Detection Using Multimodal Physiological Data54 cited
2025Intimate partner violence and stress-related disorders: from epigenomics to resilience13 cited
2026Digital Mental Health Through an Intersectional Lens: A Narrative Review3 cited