Human stress classification during public speaking using physiological signals

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Towards mental load assessment for high-risk works driven by psychophysiological data: Combining a 1D-CNN model with random forest feature selection

Hao, T., Xu, K., Zheng, X., Li, J., Chen, S., & Nie, W. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106615 · Cited by 16 · see citing works

Elicitation of Anxiety Without Time Pressure and Its Detection Using Physiological Signals and Artificial Intelligence: A Proof of Concept

Tecco, A. D., Pistolesi, F., & Lazzerini, B. (2024) · IEEE Access · doi:10.1109/access.2024.3362668 · Cited by 15 · see citing works

Designing a digital-twin based dashboard system for a flexible assembly line

Wang, K., & Lee, T.-L. (2024) · Computers & Industrial Engineering · doi:10.1016/j.cie.2024.110491 · Cited by 18 · see citing works

Feasibility of a wrist-worn wearable device for estimating mental health status in patients with mental illness

Nakagome, K., Makinodan, M., Uratani, M., Kato, M., Ozaki, N., Miyata, S., Iwamoto, K., Hashimoto, N., Toyomaki, A., Mishima, K., et al. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1189765 · Cited by 14 · see citing works

Machine Learning and Deep Learning Techniques to Detect Mental Stress Using Various Physiological Signals: A Critical Insight

Khandelwal, M., & Sharma, A. (2025) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.70035 · Cited by 14 · see citing works

A Transfer Learning-Based Framework for Enhanced Classification of Perceived Mental Stress Using EEG Spectrograms

Khan, S., Noorani, S. H., Frnda, J., Rauf, U., Arsalan, A., & Saeed, S. M. U. (2025) · IEEE Access · doi:10.1109/access.2025.3571437 · Cited by 12 · see citing works

Baseline-independent stress classification based on facial StO2

Liu, X., Chen, D., Zhou, J., & Chen, T. (2022) · Applied Intelligence · doi:10.1007/s10489-022-04041-x · Cited by 12 · see citing works

Beyond EDA: A Systematic Review of Multimodal Sympathetic Nervous System Arousal Classification for Stress Detection

Sosa, S., Fontecchio, A., Chrysikou, E. G., & Atchison, J. S. (2026) · Sensors · doi:10.3390/s26051584 · Cited by 13 · see citing works

Decoupling the role of verbal and non-verbal audience behavior on public speaking anxiety in virtual reality using behavioral and psychological measures

Girondini, M., Frigione, I., Marra, M. P., Stefanova, M., Pillan, M., Maravita, A., & Gallace, A. (2024) · Frontiers in Virtual Reality · doi:10.3389/frvir.2024.1347102 · Cited by 12 · see citing works

How can ice-breaking's "friends here, enemies there" increase the interest and enthusiasm of high school students for learning?

Darmayanti, R., Arif, V. R., Soebagyo, R. I., Ali, M., & In’am, A. (2023) · AMCA Journal of Science & Technology · doi:10.51773/ajst.v3i2.244 · Cited by 11 · see citing works

Prediction of exam scores using a multi-sensor approach for wearable exam stress dataset with uniform preprocessing

Abromavičius, V., Serackis, A., Katkevičius, A., Kazlauskas, M., & Sledević, T. (2023) · Technology and Health Care · doi:10.3233/thc-235015 · Cited by 10 · see citing works

The relationship between self-reported chronic stress, physiological stress axis dysregulation and medically-unexplained symptoms

Schulz, A., Larra, M. F., Vögele, C., Kölsch, M., & Schächinger, H. (2023) · Biological Psychology · doi:10.1016/j.biopsycho.2023.108690 · Cited by 10 · see citing works

In the Rough: Evaluation of Convergence Across Trust Assessment Techniques Using an Autonomous Golf Cart

Tenhundfeld, N. L., Forsyth, J. B., Sprague, N. R., El-Tawab, S., Cotter, J. E., & Vangsness, L. (2023) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/15553434231206422 · Cited by 8 · see citing works

Assessing the calming effects of a self-regulated inflatable vest: an evaluation based on Visual Analogue Scale and Electroencephalogram

Maula, M., Afif, I., Ammarullah, M. I., Lamura, M., Jamari, J., & Winarni, T. (2024) · Cogent Engineering · doi:10.1080/23311916.2024.2313891 · Cited by 9 · see citing works

Meningkatkan Keterampilan Public Speaking untuk Meningkatkan Kemampuan Komunikasi di Depan Umum

Prasetyo, A., Hazmin, G., Muchran, M., & Nugroho, G. S. (2023) · International Journal of Community Service Learning · doi:10.23887/ijcsl.v7i2.51633 · Cited by 8 · see citing works

Machine learning-based classification analysis of knowledge worker mental stress

Kim, H., Kim, M., Park, K., Kim, J., Yoon, D., Kim, W., & Park, C. H. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1302794 · Cited by 7 · see citing works

Stress recognition based on graph structure representation of facial StO2

Wang, J., Liu, X., Jia, Y., Chen, T., Huang, J., & Zhang, Z. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385790 · Cited by 7 · see citing works

A Novel Method for Mental Stress Assessment Based on Heart Rate Variability Analysis of Electrocardiogram Signals

Saini, S. K., & Gupta, R. (2024) · Wireless Personal Communications · doi:10.1007/s11277-024-11317-7 · Cited by 7 · see citing works

A Fusion Shallow and Deep Features Network for Facial StO2 Stress Classification

Xia, H., Sun, S., Liu, X., Zhou, J., Wang, H., & Chen, T. (2023) · IEEE Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) · doi:10.1109/itnec56291.2023.10082211 · Cited by 5 · see citing works

Mental Health Management Through Wearables and AI Innovation

Ajendla, A., Patel, M., Olikkal, P., & Vinjamuri, R. K. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-0659-9.ch010 · Cited by 3 · see citing works

Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned

Čihařová, M., Amarti, K., van Breda, W., Gevonden, M. J., Ghassemi, S., Kleiboer, A. M., Vinkers, C. H., Sep, M. S. C., Trofimova, S., Cooper, A. C., et al. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1548287 · Cited by 6 · see citing works

Machine Learning-Based Human Stress Detection Model Employing Physiological Sensory Data

Selvam, S. P., Malarvizhi, S., Ferents Koni Jiavana, K., & Ramachandran, A. S. (2025) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-024-09927-1 · Cited by 3 · see citing works

Multimodal Effort Profiles and Children's Performance: Cognitive, Physiological and Physical Dimensions

Sharma, K., Lee‐Cultura, S., Papavlasopoulou, S., & Giannakos, M. N. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70033 · Cited by 3 · see citing works

VitaStress – Multimodal Vital Signs for Stress Detection

Schreiber, P., Cinar, B., Mackert, L., & Maleshkova, M. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-94162-7_20 · Cited by 3 · see citing works

Evaluating the Potential of Wearable Technology in Early Stress Detection: A Multimodal ApproachPreprint

Darwish, B. A., Salem, N. M., Kareem, G., Mahmoud, L. N., & Sadek, I. (2024) · medRxiv · doi:10.1101/2024.07.19.24310732 · Cited by 3 · see citing works

Brain activity during a public-speaking situation in virtual reality in patients with irritable bowel syndrome and functional dyspepsia

Katsumata, R., Hosokawa, T., Manabe, N., Mori, H., Wani, K., Kimura, M., Oda, S., Ishii, K., Tanikawa, T., Urata, N., et al. (2025) · Journal of Gastroenterology · doi:10.1007/s00535-025-02228-w · Cited by 2 · see citing works

Examining the Use of Consumer Wearable Devices and Digital Tools for Stress Measurement in College Students: Scoping Review of Methods

Sathyanarayana, A., Amin, O. B., An, J., & Onnela, J.-P. “. (2026) · JMIR mhealth and uhealth · doi:10.2196/64144 · Cited by 2 · see citing works

Analysis of Physiological Response of Attention and Stress States in Teleoperation Performance of Social Tasks

Achanccaray, D., & Sumioka, H. (2023) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc40787.2023.10340007 · Cited by 2 · see citing works

Speaking face-to-face with a virtual avatar to reduce anxiety in students who stutter: Tool development and pilot study results.

Delangle, M., Moïse-Richard, A., Leclercq, A.-L., Labbé, D., Bouchard, S., Andrews, S., & Ménard, L. (2026) · Journal of Fluency Disorders · doi:10.1016/j.jfludis.2026.106194 · Cited by 1 · see citing works

SympCam: Remote Optical Measurement of Sympathetic Arousal

Braun, B., McDuff, D., Baltrušaitis, T., Streli, P., Moebus, M., & Holz, C. (2024) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi62660.2024.10913710 · Cited by 1 · see citing works

Development of a Dataset for the Evaluation of the Correlation of EDA and HRV with Stress Detection in Software Developers

Morales, J., Ruiz, E., Adolfo, E. I., García, A., Mass, J., & Mejía, F. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-97913-2_22 · Cited by 1 · see citing works

Unveiling the invisible stress: A multimodal psychological and physiological analysis of staircase evacuation under visibility loss

Lu, H., Sun, S., Zhang, X., Ge, C., Ye, R., Wang, J., Mébarki, A., Wu, J., & Yang, Y. (2025) · Safety Science · doi:10.1016/j.ssci.2025.107045 · Cited by 1 · see citing works

The effect of acute stress on the interpretability and generalization of schizophrenia predictive machine learning models

Vos, G., Ebrahimpour, M., van Eijk, L., Sarnyai, Z., & Azghadi, M. R. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.109708 · Cited by 1 · see citing works

Open challenges and future perspectives on stress-related emotions monitoring via smart wearables: A systematic literature review

Lin, H.-C., Ometov, A., Arponen, O., Nikunen, K., & Nurmi, J. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.102948 · Cited by 1 · see citing works

Detecting Anxiety Trends Using Wearable Sensor Data in Real-World Situations

Gray, M., Majumder, S., Nelson, K., & Munbodh, R. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16011-0_8 · Cited by 1 · see citing works

Multidisciplinary Investigation on How Avatars and Devices Affect Human Physiology

Kawaoka, S., Izumi, Y., Nakata, K., Haruno, M., Tanaka, T., Sumioka, H., Achanccaray, D., & Nakae, A. (2024) · Springer eBooks · doi:10.1007/978-981-97-3752-9_7 · Cited by 1 · see citing works

Human Stress Level Detection Using Hybrid Cascaded Neuro-Fuzzy SpinalNet

Lakshmi, P., Manoj Kumar, G., Smitha Vas, P., S, B. P., & Chidambaranathan, S. (2025) · Cognitive Computation · doi:10.1007/s12559-025-10471-9 · Cited by 1 · see citing works

A Study to Explore the Altered State of Consciousness Using Brain–Computer Interface (BCI)

Sharma, P. K., Dadheech, P., & Gupta, M. K. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-3991-2_28

PreSense: An IoT-Based Solution for Monitoring Anxiety in Academic Presentations

Siddiqui, S., Khan, A. A., & Dey, I. (2025) · IEEE Canada International Humanitarian Technology Conference · doi:10.1109/ihtc65087.2025.11216331

A Novel TSST-Based Multimodal Dataset for Noncontact Stress Assessment: Synchronous Integration of Computer Vision and Audio Analysis

Rafiqan, A., Setiawan, R., Sardjono, T. A., & Arif, R. E. (2025) · International Conference on Electrical, Communication, and Computer Engineering (ICECCE) · doi:10.1109/icecce67514.2025.11257984

ОБНАРУЖЕНИЕ МЕНТАЛЬНОГО АРИФМЕТИЧЕСКОГО СТРЕССА С ПОМОЩЬЮ ПОКАЗАТЕЛЕЙ ВАРИАБЕЛЬНОСТИ СЕРДЕЧНОГО РИТМАPreprint

Сергеевна, И. О., Сушков, И. А., & Владимировна, С. Е. (2025) · doi:10.24108/preprints-3114030

From Spectrum to Emotion: Machine Learning and Deep Learning in Hyperspectral Stress Detection

Khandelwal, M., & Sharma, A. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-7134-2_9

VISUALIZING STRESS AND MINDFULNESS: INTEGRATING INTELLIGENT SYSTEMS FOR EXPERIENTIAL WELL-BEING PRACTICES

Arora, S., Vaishnav, S., Sharma, A., Lone, T. A., Chib, S., & Bhise, S. (2025) · ShodhKosh Journal of Visual and Performing Arts · doi:10.29121/shodhkosh.v6.i5s.2025.6961

Quantification of Major Depressive Disorder via Spectrogram-Based Analysis of Electroencephalography Signals

Afridi, M. K., Arsalan, A., & Bibi, N. (2025) · International Multi-Topic Conference · doi:10.1109/inmic65900.2025.11348429

Integrated brain and body mechanisms underlying acute stress and trauma-related vulnerability

Lee, K. F. A., Liang, L., Asharaf, S. T., & Lee, T. M. C. (2026) · Neurobiology of Stress · doi:10.1016/j.ynstr.2026.100809

A Feasibility Study on Analyzing the Relationship Between Mental States and Music Using Physiological Signal Processing

Li, Y., & Sato-Shimokawara, E. (2026) · Communications in computer and information science · doi:10.1007/978-981-95-6739-3_22

EEG-based stress classification using time-domain features and segmentation techniques

Rauf, U., Zahid, A., Qadeer, A., Zafar, A., Khan, S., & Saeed, S. M. U. (2026) · Scientific Reports · doi:10.1038/s41598-026-50857-9

AutoStress Benchmark: Evaluating Factors that influence Cross Dataset Generalizabilty in Stress Recognition

Schreiber, P., & Maleshkova, M. (2026) · IEEE Conference on Artificial Intelligence (CAI) · doi:10.1109/cai68641.2026.11536323

MS-TFAF: A multimodal approach to distinguish students’ cognitive states during learning activities

Li, Y., Li, Y., He, X., Xiao, X., Fang, J., & Li, Y. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110877

A systematic mapping review of shared EEG signatures in stress and depression across six biomarker domains (2020–2025)

Kar, K., & Verma, G. K. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110904

EEG Signal Processing for Anxiety Detection Using Selective Spectral Coding

Bhosle, N. U., Doshi, N. A., & Biradar, S. D. (2026) · International Conference on Computing Theory and Wireless Communications (ICCTWC) · doi:10.1109/icctwc68241.2026.11582974

The Psychological Downforce Model for High Performance: Public Speaking and Entrepreneurial Pitching

Fox, G. R., & Quinn, A. (2026) · Springer eBooks · doi:10.1007/978-3-032-21528-4_5

AI Tools and Wearable Devices for Personalized Education: The DIGI-ME Approach

Meini, V., Procissi, G., Sansone, F., Diodato, G., Bachi, L., Conte, R., & Billeci, L. (2026) · IEEE International Conference on Intelligent Reality (ICIR) · doi:10.1109/icir70631.2026.11628122

A Context-Aware Framework for Optimal Filter Parameter Selection: Enhancing PRV Estimation in Wearable Wrist PPG Signals

Watanabe, Y., Yamane, N., Sathyanarayana, A., Goodwin, M. S., & Mishra, V. (2026) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3831657 · Cited by 1 · see citing works

Analysis of Mental Stress during Public Speaking Using Feature Optimization Techniques on EEG Signals

Babu, T. A., Krishna, D., Sridevi, G., Mamillu, Y., Ravi, S., & Rajesh, K. P. (2023) · CRC Press eBooks · doi:10.1201/9781003326830-4 · Cited by 1 · see citing works

Classification of Perceived Human Stress using Physiological Signals

Arsalan, A., Majid, M., Anwar, S. M., & Bağcı, U. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856377 · Cited by 37 · see citing works

A Multimodal Perceived Stress Classification Framework using Wearable Physiological SensorsPreprint

Majid, M., Arsalan, A., & Anwar, S. M. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2206.10846 · Cited by 9 · see citing works

Stress detection from speech and Galvanic Skin Response signals

Kurniawan, H., Maslov, A. V., & Pechenizkiy, M. (2013) · Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2013.6627790 · Cited by 227 · see citing works

Multimodal Personality Trait Recognition Using Wearable Sensors in Response to Public Speaking

Butt, A. R., Arsalan, A., & Majid, M. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.2976159 · Cited by 28 · see citing works