Assessing mental stress from the photoplethysmogram: a numerical study

Charlton, Peter; Celka, P.; Farukh, Bushra; Chowienczyk, Phil; Alastruey, Jordi

doi:10.1088/1361-6579/aabe6a

Cited by 101 publications

(99 citation statements)

References 62 publications

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“…Thus, an increased heart rate during mental stress leads to decreased T p , T 13 , T d , and PPG amplitude, measured at finger since less blood volume reaches the extremities. Our experimental results only partially agree with a numerical modeling study by Charlton et al [12]. Charlton et al did not find any relation between PPG signal amplitude and stress.…”

Section: Discussionsupporting

confidence: 73%

“…However, the effect size of T 13 is significantly less than that of diastolic duration T d during the arithmetic task AT stage. This might be related to the de-tection of the diastolic wave as proposed by [12] in presence of artifacts, where a local maxima is searched in the PPG and not always in the second derivative.…”

Section: Discussionmentioning

confidence: 99%

“…The calculation of the first three PPG signal derivatives was required for finding the positions of the extremas (a, b, c, d, e and f ) in the second and third signal derivatives which subsequently were used for estimation of six features ( Figure 3). Extremity point locations were detected using the methodology proposed by Charlton [12]. The pulse was defined only if all six extremities were found.…”

Section: Morphological Parametersmentioning

confidence: 99%

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Photoplethysmogram Signal Morphology-Based Stress Assessment

Rinkevičius¹,

Kontaxis²,

Gil³

et al. 2019

Computing in Cardiology Conference (CinC)

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Stress is a healthy natural response to a perceived or actual threat. However, when stress is persistent, it may decrease work productivity, increase the risk of diseases, and affect the quality of life. Stress is reflected in physiological variables, such as heart rate, blood pressure, and pulse wave velocity among others. A photoplethysmogram (PPG) contains information related to pulse rate and blood pressure. This study analyses parameters derived from PPG signal morphology for mental stress assessment.A low-complexity algorithm is designed using bandpass filtered higher-order derivatives of the PPG signal for estimation of six morphological parameters: the forward pulse wave amplitude A 1 , the systole and diastole durations T 1 and T d , the time delays of reflected waves T 12 and T 13 from the renal and iliac sites in the central arteries, and the pulse duration T p . The parameters were investigated on a set of 18 healthy subjects by using a modified Trier Social Stress Test.The results show that the most sensitive PPG morphology parameters to mental stress are the amplitude of forward wave A 1 , the duration of diastole T d , the time delay of the reflected wave T 13 , and the pulse-to-pulse interval T p .

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Section: Discussionsupporting

confidence: 73%

Section: Discussionmentioning

confidence: 99%

Section: Morphological Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Photoplethysmogram Signal Morphology-Based Stress Assessment

Rinkevičius¹,

Kontaxis²,

Gil³

et al. 2019

Computing in Cardiology Conference (CinC)

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“…Pulse waves were identified using the algorithm described in [9]. Pulse wave analysis techniques were used to extract 31 vascular stiffness indices (termed VRR indices) and HR from each PPG pulse wave, as described in [10]. These time series were median filtered to attenuate high frequency variations (using a filter of order 15 beats).…”

Section: Extracting Vascular Recovery Rate (Vrr) Indices From the Ppgmentioning

confidence: 99%

Measuring Vascular Recovery Rate After Exercise

Dijab

Alastruey

Charlton

2018

5th International Electronic Conference on Sensors and Applications

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The rate at which an individual recovers from exercise is known to be indicative of cardiovascular risk. It has been widely shown that the reduction in heart rate immediately after exercise is predictive of mortality. However, little research has been conducted into whether the time taken for the blood vessels to return to normal is also indicative of risk. In this study, we present a novel approach to assess vascular recovery rate (VRR) using the photoplethysmogram (PPG) signal, which is monitored by smart wearables. The VORTAL dataset (http://peterhcharlton.github.io/RRest/) was used for this study, containing PPG signals from 39 healthy subjects before (baseline) and after exercise. 31 VRR indices were extracted from the PPG pulse wave shape, as well as heart rate for comparison. The rate at which indices returned to baseline after exercise was quantified, and the consistency of changes between subjects was assessed statistically. Many VRR indices exhibited changes after exercise which were consistent between subjects. Indices derived from the timings and second derivative of pulse waves were identified as candidates for future work. The rate at which the indices returned to baseline differed between indices and subjects, indicating that they may provide additional information beyond that of heart rate, and that they may be useful for stratifying subjects. This study demonstrated the feasibility of assessing VRR after exercise from the PPG. Future studies should investigate whether VRR indices are associated with cardiovascular fitness, and the potential utility of incorporating the indices into wearable sensors.

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“…9 Recently, there has been a plethora of interest in extending the application of PPG beyond pulse oximetry, for example, in the assessment of vascular mechanics, heart rate, blood pressure, tissue perfusion, respiration, and mental stress. [10][11][12][13][14][15][16] To continuously monitor the intestinal perfusion and oxygenation, an endocavitary PPG sensor has been proposed. 17 The proposed sensor can be inserted through the anal orifice of a patient to capture the PPG signal by illuminating the colon utilizing light emitters of dual wavelength, corresponding to red and infrared.…”

Section: Introductionmentioning

confidence: 99%

In silico and in vivo investigations using an endocavitary photoplethysmography sensor for tissue viability monitoring

et al. 2020

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In silico and in vivo investigations using an endocavitary photoplethysmography sensor for tissue viability monitoring," J. AbstractSignificance: Colorectal cancer is one of the major causes of cancer-related deaths worldwide. Surgical removal of the cancerous growth is the primary treatment for this disease. A colorectal cancer surgery, however, is often unsuccessful due to the anastomotic failure that may occur following the surgical incision. Prevention of an anastomotic failure requires continuous monitoring of intestinal tissue viability during and after colorectal surgery. To date, no clinical technology exists for the dynamic and continuous monitoring of the intestinal perfusion.Aim: A dual-wavelength indwelling bowel photoplethysmography (PPG) sensor for the continuous monitoring of intestinal viability was proposed and characterized through a set of in silico and in vivo investigations.Approach: The in silico investigation was based on a Monte Carlo model that was executed to quantify the variables such as penetration depth and detected intensity with respect to the sensortissue separations and tissue perfusion. Utilizing the simulated information, an indwelling reflectance PPG sensor was designed and tested on 20 healthy volunteers. Two sets of in vivo studies were performed using the driving current intensities 20 and 40 mA for a comparative analysis, using buccal tissue as a proxy tissue-site.Results: Both simulated and experimental results showed the efficacy of the sensor to acquire good signals through the "contact" to a "noncontact" separation of 5 mm. A very slow wavelength-dependent variation was shown in the detected intensity at the normal and hypoxic states of the tissue, whereas a decay in the intensity was found with the increasing submucosal-blood volume. The simulated detected-to-incident-photon-ratio and the experimental signal-to-noise ratio exhibited strong positive correlations, with the Pearson product-moment correlation coefficient R ranging between 0.65 and 0.87. Conclusions:The detailed feasibility analysis presented will lead to clinical trials utilizing the proposed sensor.

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Assessing mental stress from the photoplethysmogram: a numerical study

Cited by 101 publications

References 62 publications

Photoplethysmogram Signal Morphology-Based Stress Assessment

Photoplethysmogram Signal Morphology-Based Stress Assessment

Measuring Vascular Recovery Rate After Exercise

In silico and in vivo investigations using an endocavitary photoplethysmography sensor for tissue viability monitoring

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