Photoplethysmographic logger with contact force and hydrostatic pressure monitoring

Santos, Pedro; Almeida, Vânia; Cardoso, J. M. R.; Correia, C.M.B.A.

doi:10.1109/enbeng.2013.6518437

Cited by 5 publications

(4 citation statements)

References 39 publications

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“…There is a 4.19% to 4.76% deviation between the content of blood oxygen derived from the two curves, and the impact of the pressure can induce a variation of 0.35% to 6.2%. The presented data matches findings from previous research [44] (in small loads, Santos' study demonstrated a 7% variation, utilizing wavelengths of 660 nm and 905 nm; Similarly, Dresher's research yielded a result of 5.1%). When setting up the empirical calibration curve for oximetry, it is imperative to consider the impact of this pressure-induced variation.…”

Section: Oxygen Saturation Analysissupporting

confidence: 89%

The effect of contact pressure on photoplethysmography

Gong,

Yu,

Xuan

2024

IJEECS

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In the bioinformation photoplethysmography (PPG) measurement, the precision and repeatability could be impacted by the contact pressure between the optical sensor and the measurement site. Taking the finger’s geometrical, mechanical, and optical characteristics into consideration, finite element models and Monte Carlo (MC) simulation methods were used to quantitatively analyze the effects of the deformation of different finger layers under contact pressure on its optical parameters and PPG signals during fingertip spectroscopic detection. Firstly, a 3D axisymmetric finger model was established, pelican optimization was used to find the parameter lamp that caused the simulation to best match the finger pressing behavior, modeled the deformation of each layer, and quantified the changes in their absorption and scattering coefficient. Then, before and after pressure application, photon propagation in the reflectance and transmittance modalities within the diastolic and systolic finger tissues at 660 nm and 940 nm were studied by MC simulation. The result shows that contact pressure significantly altered the thickness of the dermis and subcutaneous tissues, a decrease in tissue thickness caused an increase in optical coefficient, which resulted in a reduction in normalized pulsatile reflectance and a boost in transmittance, and the change was dependent on wavelength.

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Section: Oxygen Saturation Analysissupporting

confidence: 89%

The effect of contact pressure on photoplethysmography

Gong,

Yu,

Xuan

2024

IJEECS

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“…This band would apply a skin pressure of about 75 mmHg and, due to its compliance, it would hold steady the applied pressure while the finger was in different positions. Another force measuring modality to integrate with a PPG sensor is a Force Sensing Resistor (FSR, Interlink Electronics, Camarillo, CA, USA), as done by Santos et al [ 214 ]. Liu et al implemented a fiber Bragg gating to measure applied pressure [ 215 ].…”

Section: External Factorsmentioning

confidence: 99%

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

et al. 2021

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Photoplethysmography (PPG) is a low-cost, noninvasive optical technique that uses change in light transmission with changes in blood volume within tissue to provide information for cardiovascular health and fitness. As remote health and wearable medical devices become more prevalent, PPG devices are being developed as part of wearable systems to monitor parameters such as heart rate (HR) that do not require complex analysis of the PPG waveform. However, complex analyses of the PPG waveform yield valuable clinical information, such as: blood pressure, respiratory information, sympathetic nervous system activity, and heart rate variability. Systems aiming to derive such complex parameters do not always account for realistic sources of noise, as testing is performed within controlled parameter spaces. A wearable monitoring tool to be used beyond fitness and heart rate must account for noise sources originating from individual patient variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external perturbations of the device itself (e.g., motion artifact, ambient light, and applied pressure to the skin). Here, we present a comprehensive review of the literature that aims to summarize these noise sources for future PPG device development for use in health monitoring.

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“…The PPG was recorded with a custom made probe and front end circuit [29] that contains a red and infrared LED but only the red channel was used. The electrical signal was then digitized with a National Instruments data acquisition device (NI-DAQ 6210) connect to the host PC.…”

Section: In Vivo Testmentioning

confidence: 99%

Which wavelength is the best for arterial pulse waveform extraction using laser speckle imaging?

Vaz

Pereira

Figueiras

et al. 2016

Biomedical Signal Processing and Control

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a b s t r a c tA multi-wavelengths analysis for pulse waveform extraction using laser speckle is conducted. The proposed system consists of three coherent light sources (532 nm, 635 nm, 850 nm). A bench-test composed of a moving skin-like phantom (silicone membrane) is used to compare the results obtained from different wavelengths. The system is able to identify a skin-like phantom vibration frequency, within physiological values, with a minimum error of 0.5 mHz for the 635 nm and 850 nm wavelengths and a minimum error of 1.3 mHz for the 532 nm light wavelength using a FFT-based algorithm. The phantom velocity profile is estimated with an error ranging from 27% to 9% using a bidimensional correlation coefficient-based algorithm. An in vivo trial is also conducted, using the 532 nm and 635 nm laser sources. The 850 nm light source has not been able to extract the pulse waveform. The heart rate is identified with a minimum error of 0.48 beats per minute for the 532 nm light source and a minimal error of 1.15 beats per minute for the 635 nm light source. Our work reveals that a laser speckle-based system with a 532 nm wavelength is able to give arterial pulse waveform with better results than those given with a 635 nm laser.

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Photoplethysmographic logger with contact force and hydrostatic pressure monitoring

Cited by 5 publications

References 39 publications

The effect of contact pressure on photoplethysmography

The effect of contact pressure on photoplethysmography

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

Which wavelength is the best for arterial pulse waveform extraction using laser speckle imaging?

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