Dataset of Pulse Waves at Six Levels of Mental Stress
The full database can be downloaded from the supplementary data section (immediately after the abstract)
of the journal website where this work was published. Matlab functions for processing and analysing the data are also provided.
Mental stress is detrimental to cardiovascular health. Using Nektar1D, we created a dataset of simulated pulse waves at six levels of mental stress. This was achieved by changing the model input parameters both simultaneously and individually, in accordance with haemodynamic changes associated with stress, as detailed by Charlton et al. (Physiol Meas, 2018). For each stress level, blood pressure, blood flow, luminal cross-sectional area and PPG waves are provided at the following measurement sites: ankle, aortic root, brachial, carotid, digital, femoral, radial and temporal. PPG waves were estimated from blood pressure waves using a transfer function. Several features extracted from the PPG waves at the brachial, radial and temporal sites exhibited significant trends with stress and have the potential to be used to monitor stress in healthcare and consumer devices. These trends were also seen in an in vivo study by Celka et al. (Healthc Technol Lett, 2020).
Assessing mental stress from the photoplethysmogram: a numerical study.
Physiological Measurement
39(5), 054001, 2018.
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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