ArticleSensors (Basel, Switzerland)2022
Stress Monitoring Using Wearable Sensors: A Pilot Study and Stress-Predict Dataset.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Influence of eHealth Stress Management Interventions on Psychological Health Parameters in Patients With Cardiovascular Disease: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- When Wellness Stress Detection Enters Healthcare Workflows: An Iso-Heart-Rate, Cross-Corpus Evaluation of Wrist Wearables.Healthcare (Basel, Switzerland) · 2026Article
- BreathSense: A Two-Stage Digital Framework for Student Stress Monitoring Using Personalized Breath-VOC Thresholding and In-the-Wild Validation.Behavioral sciences (Basel, Switzerland) · 2026Article
- Mental Stress Detection Using Physiological Sensors and Artificial Intelligence: A Review.Sensors (Basel, Switzerland) · 2026Review
- Article
- Development and Validation of a Multimodal Wearable Belt for Abdominal Biosignal Monitoring with Application to Irritable Bowel Syndrome.Micromachines · 2025Article
- A Scoping Review of Studies Reporting Heart Rate Variability Measurement Among Pregnant and Postpartum People Using Wearable Technology.Biological research for nursing · 2025Article
- A Co-Segmentation Algorithm to Predict Emotional Stress From Passively Sensed mHealth Data.Statistics in medicine · 2025Article
- A Wearable Molecularly Imprinted Electrochemical Sensor for Cortisol Stable Monitoring in Sweat.Biosensors · 2025Article
- A multi-modal deep learning approach for stress detection using physiological signals: integrating time and frequency domain features.Frontiers in physiology · 2025Article
- Examining the challenges of blood pressure estimation via photoplethysmogram.Scientific reports · 2024Article
- Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.JMIR mHealth and uHealth · 2024Observational
- Personalized Stress Detection Using Biosignals from Wearables: A Scoping Review.Sensors (Basel, Switzerland) · 2024Article
- Predicting stress in first-year college students using sleep data from wearable devices.PLOS digital health · 2024Article
- Advances in electrochemical biosensor design for the detection of the stress biomarker cortisol.Analytical and bioanalytical chemistry · 2024Review
- Mental Health for All: The Case for Investing in Digital Mental Health to Improve Global Outcomes, Access, and Innovation in Low-Resource Settings.Journal of clinical medicine · 2023Review
- Wrist-Based Electrodermal Activity Monitoring for Stress Detection Using Federated Learning.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
With the recent advancements in the field of wearable technologies, the opportunity to monitor stress continuously using different physiological variables has gained significant interest. The early detection of stress can help improve healthcare and minimizes the negative impact of long-term stress. This paper reports outcomes of a pilot study and associated stress-monitoring dataset, named the "Stress-Predict Dataset", created by collecting physiological signals from healthy subjects using wrist-worn watches with a photoplethysmogram (PPG) sensor. While wearing these watches, 35 healthy volunteers underwent a series of tasks (i.e., Stroop color test, Trier Social Stress Test and Hyperventilation Provocation Test), along with a rest period in-between each task. They also answered questionnaires designed to induce stress levels compatible with daily life. The changes in the blood volume pulse (BVP) and heart rate were recorded by the watch and were labelled as occurring during stress-inducing tasks or a rest period (no stress). Additionally, respiratory rate was estimated using the BVP signal. Statistical models and personalised adaptive reference ranges were used to determine the utility of the proposed stressors and the extracted variables (heart rate and respiratory rate). The analysis showed that the interview session was the most significant stress stimulus, causing a significant variation in heart rate of 27 (77%) participants and respiratory rate of 28 (80%) participants out of 35. The outcomes of this study contribute to the understanding the role of stressors and their association with physiological response and provide a dataset to help develop new wearable solutions for more reliable, valid, and sensitive physio-logical stress monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.