Trial reportSensors (Basel, Switzerland)2018
Portable System for Real-Time Detection of Stress Level.
Trial report in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 97 citations in OpenAlex.
- Channel-Dependent Multilayer EEG Time-Frequency Representations Combined with Transfer Learning-Based Deep CNN Framework for Few-Channel MI EEG Classification.Bioengineering (Basel, Switzerland) · 2025Article
- Neurocardiac signatures of acute mental stress: a sex-comparative study.Frontiers in neuroscience · 2025Article
- Low-Cost EEG Multi-Subject Recording Platform for the Assessment of Students' Attention and the Estimation of Academic Performance in Secondary School.Sensors (Basel, Switzerland) · 2023Article
- Recent Advances in Multiplexed Wearable Sensor Platforms for Real-Time Monitoring Lifetime Stress: A Review.Biosensors · 2023Review
- Wearables measuring electrodermal activity to assess perceived stress in care: a scoping review.Acta neuropsychiatrica · 2023Review
- AI-Enabled Smart Wristband Providing Real-Time Vital Signs and Stress Monitoring.Sensors (Basel, Switzerland) · 2023Article
- Measuring Biosignals with Single Circuit Boards.Bioengineering (Basel, Switzerland) · 2022Review
- Real-time mental stress detection using multimodality expressions with a deep learning framework.Frontiers in neuroscience · 2022Article
- A Review on Mental Stress Assessment Methods Using EEG Signals.Sensors (Basel, Switzerland) · 2021Review
- Discrimination of simultaneous psychological and physical stressors using wristband biosignals.Computer methods and programs in biomedicine · 2021Article
- Article
- Classifying Multi-Level Stress Responses From Brain Cortical EEG in Nurses and Non-Health Professionals Using Machine Learning Auto Encoder.IEEE journal of translational engineering in health and medicine · 2021Article
- Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring.Frontiers in digital health · 2021Review
- Virtual Reality as a Portable Alternative to Chromotherapy Rooms for Stress Relief: A Preliminary Study.Sensors (Basel, Switzerland) · 2020Article
- Real-Time Stress Assessment Using Sliding Window Based Convolutional Neural Network.Sensors (Basel, Switzerland) · 2020Article
- An Effective Mental Stress State Detection and Evaluation System Using Minimum Number of Frontal Brain Electrodes.Diagnostics (Basel, Switzerland) · 2020Article
- Stress Detection via Keyboard Typing Behaviors by Using Smartphone Sensors and Machine Learning Techniques.Journal of medical systems · 2020Article
- Portable Drowsiness Detection through Use of a Prefrontal Single-Channel Electroencephalogram.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Currently, mental stress is a major problem in our society. It is related to a wide variety of diseases and is mainly caused by daily-life factors. The use of mobile technology for healthcare purposes has dramatically increased during the last few years. In particular, for out-of-lab stress detection, a considerable number of biosignal-based methods and systems have been proposed. However, these approaches have not matured yet into applications that are reliable and useful enough to significantly improve people's quality of life. Further research is needed. In this paper, we propose a portable system for real-time detection of stress based on multiple biosignals such as electroencephalography, electrocardiography, electromyography, and galvanic skin response. In order to validate our system, we conducted a study using a previously published and well-established methodology. In our study, ten subjects were stressed and then relaxed while their biosignals were simultaneously recorded with the portable system. The results show that our system can classify three levels of stress (stress, relax, and neutral) with a resolution of a few seconds and 86% accuracy. This suggests that the proposed system could have a relevant impact on people's lives. It can be used to prevent stress episodes in many situations of everyday life such as work, school, and home.
Indexed as
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What OpenQuestion holds
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.