ArticlePhysiological measurement2018
Assessing mental stress from the photoplethysmogram: a numerical study.
Article in Physiological measurement, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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The trial behind it
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Who cites it
52 citing papers in PubMed, 133 citations in OpenAlex.
- Hypertension screening via awake-sleep differences in photoplethysmogram signals.European heart journal. Digital health · 2026Article
- Assessing Mental Health and Emotional States by Using Smartphone Photoplethysmography-Based Digital Pulse Waveform Analysis: Cross-Sectional Observational Study.JMIR mHealth and uHealth · 2026Observational
- [A multi-source information fusion-based method for the local pulse wave velocity estimation in carotid artery].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Article
- Pulse Wave Velocity Estimation in a Controlled In Vitro Vascular Model: Benchmarking Machine Learning Approaches.Sensors (Basel, Switzerland) · 2026Article
- Article
- Feasibility of heart rate monitoring in hemodialysis patients using visible imaging: a pilot study.Frontiers in physiology · 2026Article
- Prediction of Cardiovascular Disease Events From the Photoplethysmograph Waveform.Journal of the American Heart Association · 2025Article
- Physiological and Personality Measures as Potential Factors Associated with Cardiac Coherence Training Effects on Symptoms Reduction: A Pilot Study on Healthcare Workers.Clinical neuropsychiatry · 2025Article
- A Multimodal System for Comprehensive Cardiovascular Monitoring Using ECG, PCG, and PPG Signal Fusion.Sensors (Basel, Switzerland) · 2025Article
- Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Machine Learning-Based VOBiosensors · 2025Article
- A finger on the pulse of cardiovascular health: estimating blood pressure with smartphone photoplethysmography-based pulse waveform analysis.Biomedical engineering online · 2025Article
- From the latin "re-cordis, passing through the heart": autonomic modulation differentiates migraineurs from controls when recounting a significant life event.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Article
- Developing technologies to assess vascular ageing: a roadmap from VascAgeNet.Physiological measurement · 2024Review
- Review
- Development of a Personalized Multiclass Classification Model to Detect Blood Pressure Variations Associated with Physical or Cognitive Workload.Sensors (Basel, Switzerland) · 2024Article
- pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis.Physiological measurement · 2024Article
- Real-Time Classification of Anxiety in Virtual Reality Therapy Using Biosensors and a Convolutional Neural Network.Biosensors · 2024Article
- A Novel Respiratory Rate Estimation Algorithm from Photoplethysmogram Using Deep Learning Model.Diagnostics (Basel, Switzerland) · 2024Article
- Robust arterial compliance estimation with Katz's fractal dimension of photoplethysmography.Frontiers in physiology · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
objectiveMental stress is detrimental to cardiovascular health, being a risk factor for coronary heart disease and a trigger for cardiac events. However, it is not currently routinely assessed. The aim of this study was to identify features of the photoplethysmogram (PPG) pulse wave which are indicative of mental stress. APPROACH: A numerical model of pulse wave propagation was used to simulate blood pressure signals, from which simulated PPG pulse waves were estimated using a transfer function. Pulse waves were simulated at six levels of stress by changing the model input parameters both simultaneously and individually, in accordance with haemodynamic changes associated with stress. Thirty-two feature measurements were extracted from pulse waves at three measurement sites: the brachial, radial and temporal arteries. Features which changed significantly with stress were identified using the Mann-Kendall monotonic trend test. MAIN
resultsSeventeen features exhibited significant trends with stress in measurements from at least one site. Three features showed significant trends at all three sites: the time from pulse onset to peak, the time from the dicrotic notch to pulse end, and the pulse rate. More features showed significant trends at the radial artery (15) than the brachial (8) or temporal (7) arteries. Most features were influenced by multiple input parameters. SIGNIFICANCE: The features identified in this study could be used to monitor stress in healthcare and consumer devices. Measurements at the radial artery may provide superior performance than the brachial or temporal arteries. In vivo studies are required to confirm these observations.
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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.