ArticleJournal of medical systems2020
Stress Detection via Keyboard Typing Behaviors by Using Smartphone Sensors and Machine Learning Techniques.
Article in Journal of medical systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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
11 citing papers in PubMed.
- Integrating Artificial Intelligence with Wearable Sensors for Advanced Health Monitoring and Diagnosis.Biosensors · 2026Review
- Stress and Emotion Open Access Data: A Review on Datasets, Modalities, Methods, Challenges, and Future Research Perspectives.Journal of healthcare informatics research · 2025Review
- Modern Smart Gadgets and Wearables for Diagnosis and Management of Stress, Wellness, and Anxiety: A Comprehensive Review.Healthcare (Basel, Switzerland) · 2025Review
- QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals.Scientific reports · 2024Article
- Article
- A New Perspective on Stress Detection: An Automated Approach for Detecting Eustress and Distress.IEEE transactions on affective computing · 2023Article
- K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels.Scientific data · 2023Article
- In Search of State and Trait Emotion Markers in Mobile-Sensed Language: Field Study.JMIR mental health · 2022Article
- Pain and Stress Detection Using Wearable Sensors and Devices-A Review.Sensors (Basel, Switzerland) · 2021Review
- Evaluating the Reproducibility of Physiological Stress Detection Models.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2020Article
- Assessing healthcare service quality using routinely collected data: Linking information systems in emergency care.Journal of medical systems · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stress is one of the biggest problems in modern society. It may not be possible for people to perceive if they are under high stress or not. It is important to detect stress early and unobtrusively. In this context, stress detection can be considered as a classification problem. In this study, it was investigated the effects of stress by using accelerometer and gyroscope sensor data of the writing behavior on a smartphone touchscreen panel. For this purpose, smartphone data including two states (stress and calm) were collected from 46 participants. The obtained sensor signals were divided into 5, 10 and 15 s interval windows to create three different data sets and 112 different features were defined from the raw data. To obtain more effective feature subsets, these features were ranked by using Gain Ratio feature selection algorithm. Afterwards, writing behaviors were classified by C4.5 Decision Trees, Bayesian Networks and k-Nearest Neighbor methods. As a result of the experiments, 74.26%, 67.86%, and 87.56% accuracy classification results were obtained respectively.
Indexed as
Identifiers
32072331What 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.