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      Assessing mental stress from the photoplethysmogram: a numerical study

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          Abstract

          Objective: Mental 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 results : Seventeen 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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          Psychological stress and cardiovascular disease.

          There is an enormous amount of literature on psychological stress and cardiovascular disease. This report reviews conceptual issues in defining stress and then explores the ramifications of stress in terms of the effects of acute versus long-term stressors on cardiac functioning. Examples of acute stressor studies are discussed in terms of disasters (earthquakes) and in the context of experimental stress physiology studies, which offer a more detailed perspective on underlying physiology. Studies of chronic stressors are discussed in terms of job stress, marital unhappiness, and burden of caregiving. From all of these studies there are extensive data concerning stressors' contributions to diverse pathophysiological changes including sudden death, myocardial infarction, myocardial ischemia, and wall motion abnormalities, as well as to alterations in cardiac regulation as indexed by changes in sympathetic nervous system activity and hemostasis. Although stressors trigger events, it is less clear that stress "causes" the events. There is nonetheless overwhelming evidence both for the deleterious effects of stress on the heart and for the fact that vulnerability and resilience factors play a role in amplifying or dampening those effects. Numerous approaches are available for stress management that can decrease patients' suffering and enhance their quality of life.
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            Emergency duties and deaths from heart disease among firefighters in the United States.

            Heart disease causes 45% of the deaths that occur among U.S. firefighters while they are on duty. We examined duty-specific risks of death from coronary heart disease among on-duty U.S. firefighters from 1994 to 2004. We reviewed summaries provided by the Federal Emergency Management Agency of the deaths of all on-duty firefighters between 1994 and 2004, except for deaths associated with the September 11, 2001, terrorist attacks. Estimates of the proportions of time spent by firefighters each year performing various duties were obtained from a municipal fire department, from 17 large metropolitan fire departments, and from a national database. Odds ratios and 95% confidence intervals for death from coronary heart disease during specific duties were calculated from the ratios of the observed odds to the expected odds, with nonemergency duties as the reference category. Deaths from coronary heart disease were associated with suppressing a fire (32.1% of all such deaths), responding to an alarm (13.4%), returning from an alarm (17.4%), engaging in physical training (12.5%), responding to nonfire emergencies (9.4%), and performing nonemergency duties (15.4%). As compared with the odds of death from coronary heart disease during nonemergency duties, the odds were 12.1 to 136 times as high during fire suppression, 2.8 to 14.1 times as high during alarm response, 2.2 to 10.5 times as high during alarm return, and 2.9 to 6.6 times as high during physical training. These odds were based on three estimates of the time that firefighters spend on their duties. Certain emergency firefighting duties were associated with a risk of death from coronary heart disease that was markedly higher than the risk associated with nonemergency duties. Fire suppression was associated with the highest risk, which was approximately 10 to 100 times as high as that for nonemergency duties. Copyright 2007 Massachusetts Medical Society.
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              Objective measures, sensors and computational techniques for stress recognition and classification: a survey.

              Stress is a major growing concern in our day and age adversely impacting both individuals and society. Stress research has a wide range of benefits from improving personal operations, learning, and increasing work productivity to benefiting society - making it an interesting and socially beneficial area of research. This survey reviews sensors that have been used to measure stress and investigates techniques for modelling stress. It discusses non-invasive and unobtrusive sensors for measuring computed stress, a term we coin in the paper. Sensors that do not impede everyday activities that could be used by those who would like to monitor stress levels on a regular basis (e.g. vehicle drivers, patients with illnesses linked to stress) is the focus of the discussion. Computational techniques have the capacity to determine optimal sensor fusion and automate data analysis for stress recognition and classification. Several computational techniques have been developed to model stress based on techniques such as Bayesian networks, artificial neural networks, and support vector machines, which this survey investigates. The survey concludes with a summary and provides possible directions for further computational stress research.
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                Author and article information

                Journal
                Physiol Meas
                Physiol Meas
                pmea
                PMEAE3
                Physiological Measurement
                IOP Publishing
                0967-3334
                1361-6579
                May 2018
                15 May 2018
                : 39
                : 5
                : 054001
                Affiliations
                [1 ]Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London , King’s Health Partners, St Thomas’ Hospital, London, SE1 7EH, United Kingdom
                [2 ]Polar Electro Oy , Professorintie 5, 90440 Kempele, Finland
                [3 ]Department of Clinical Pharmacology, King’s College London , King’s Health Partners, St Thomas’ Hospital, London, SE1 7EH, United Kingdom
                peter.charlton@ 123456kcl.ac.uk
                Author information
                http://orcid.org/0000-0003-3836-8655
                http://orcid.org/0000-0003-3742-5259
                Article
                pmeaaabe6a aabe6a PMEA-102383.R1
                10.1088/1361-6579/aabe6a
                5964362
                29658894
                9acbd5b0-2fee-4e95-8179-7d4b0a105620
                © 2018 Institute of Physics and Engineering in Medicine

                Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

                History
                : 27 January 2018
                : 26 March 2018
                : 16 April 2018
                : 4 April 2018
                : 15 May 2018
                Page count
                Pages: 15
                Funding
                Funded by: British Heart Foundation https://doi.org/10.13039/501100000274
                Award ID: PG/15/104/31913
                Funded by: Wellcome Trust https://doi.org/10.13039/100004440
                Award ID: WT 203148/Z/16/Z
                Funded by: Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266
                Award ID: WT 203148/Z/16/Z
                Categories
                Paper
                Focus on Analysis and Measurement of the Arterial Pulse Wave Waveform
                Custom metadata
                yes

                biomedical signal processing,photoplethysmogram,mental stress,1d modelling,pulse wave propagation

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