In the last decades, photoplethysmography (PPG) has been used as a noninvasive technique for monitoring arterial oxygen saturation by pulse oximetry (PO), whereas near-infrared spectroscopy (NIRS) ...has been employed for monitoring tissue blood perfusion. While NIRS offers more parameters to evaluate oxygen delivery and consumption in deep tissues, PO only assesses the state of oxygen delivery. For a broader assessment of blood perfusion, this paper explores the utilization of dual-wavelength PPG by using the pulsatile (ac) and continuous (dc) PPG for the estimation of arterial oxygen saturation (SpO2) by conventional PO. Additionally, the Beer-Lambert law is applied to the dc components only for the estimation of changes in deoxyhemoglobin (HHb), oxyhemoglobin (HbO2), and total hemoglobin (tHb) as in NIRS. The system was evaluated on the forearm of 21 healthy volunteers during induction of venous occlusion (VO) and total occlusion (TO). A reflectance PPG probe and NIRS sensor were applied above the brachioradialis, PO sensors were applied on the fingers, and all the signals were acquired simultaneously. While NIRS and forearm SpO2 indicated VO, SpO2 from the finger did not exhibit any significant drop from baseline. During TO, all the indexes indicated the change in blood perfusion. HHb, HbO2, and tHb changes estimated by PPG presented high correlation with the same parameters obtained by NIRS during VO (r 2 = 0.960, r 2 = 0.821, and r 2 = 0.974, respectively) and during TO (r 2 = 0.988, r 2 = 0.940, and r 2 = 0.938, respectively). The system demonstrated the ability to extract valuable information from PPG signals for a broader assessment of tissue blood perfusion.
Introduction:
Heart Rate Variability (HRV) and Pulse Rate Variability (PRV), are non-invasive techniques for monitoring changes in the cardiac cycle. Both techniques have been used for assessing the ...autonomic activity. Although highly correlated in healthy subjects, differences in HRV and PRV have been observed under various physiological conditions. The reasons for their disparities in assessing the degree of autonomic activity remains unknown.
Methods:
To investigate the differences between HRV and PRV, a whole-body cold exposure (CE) study was conducted on 20 healthy volunteers (11 male and 9 female, 30.3 ± 10.4 years old), where PRV indices were measured from red photoplethysmography signals acquired from central (ear canal, ear lobe) and peripheral sites (finger and toe), and HRV indices from the ECG signal. PRV and HRV indices were used to assess the effects of CE upon the autonomic control in peripheral and core vasculature, and on the relationship between HRV and PRV. The hypotheses underlying the experiment were that PRV from central vasculature is less affected by CE than PRV from the peripheries, and that PRV from peripheral and central vasculature differ with HRV to a different extent, especially during CE.
Results:
Most of the PRV time-domain and Poincaré plot indices increased during cold exposure. Frequency-domain parameters also showed differences except for relative-power frequency-domain parameters, which remained unchanged. HRV-derived parameters showed a similar behavior but were less affected than PRV. When PRV and HRV parameters were compared, time-domain, absolute-power frequency-domain, and non-linear indices showed differences among stages from most of the locations. Bland-Altman analysis showed that the relationship between HRV and PRV was affected by CE, and that it recovered faster in the core vasculature after CE.
Conclusion:
PRV responds to cold exposure differently to HRV, especially in peripheral sites such as the finger and the toe, and may have different information not available in HRV due to its non-localized nature. Hence, multi-site PRV shows promise for assessing the autonomic activity on different body locations and under different circumstances, which could allow for further understanding of the localized responses of the autonomic nervous system.
Photoplethysmography (PPG) signals from the forehead can be used in pulse oximetry as they are less affected by vasoconstriction compared to fingers. However, the increase in venous blood caused by ...the positioning of the patient can deteriorate the signals and cause erroneous estimations of the arterial oxygen saturation. To date, there is no method to measure this venous presence under the PPG sensor. This study investigates the feasibility of using PPG signals from the forehead in an effort to estimate relative changes in haemoglobin concentrations that could reveal these posture-induced changes. Two identical reflectance PPG sensors were placed on two different positions on the forehead (above the eyebrow and on top of a large vein) in 16 healthy volunteers during a head-down tilt protocol. Relative changes in oxygenated ( Δ HbO 2 ), reduced ( Δ HHb) and total ( Δ tHb) haemoglobin were estimated from the PPG signals and the trends were compared with reference Near Infrared Spectroscopy (NIRS) measurements. Also, the signals from the two PPG sensors were analysed in order to reveal any difference due to the positioning of the sensor. Δ HbO 2 , Δ HHb and Δ tHb estimated from the forehead PPGs trended well with the same parameters from the reference NIRS. However, placing the sensor over a large vasculature reduces trending against NIRS, introduces biases as well as increases the variability of the changes in Δ HHb. Forehead PPG signals can be used to measure perfusion changes to reveal venous pooling induced by the positioning of the subject. Placing the sensor above the eyebrow and away from large vasculature avoids biases and large variability in the measurements.
Purpose
In this research, a non-invasive intracranial pressure (nICP) optical sensor was developed and evaluated in a clinical pilot study. The technology relied on infrared light to probe brain ...tissue, using photodetectors to capture backscattered light modulated by vascular pulsations within the brain’s vascular tissue. The underlying hypothesis was that changes in extramural arterial pressure could affect the morphology of recorded optical signals (photoplethysmograms, or PPGs), and analysing these signals with a custom algorithm could enable the non-invasive calculation of intracranial pressure (nICP).
Methods
This pilot study was the first to evaluate the nICP probe alongside invasive ICP monitoring as a gold standard. nICP monitoring occurred in 40 patients undergoing invasive ICP monitoring, with data randomly split for machine learning. Quality PPG signals were extracted and analysed for time-based features. The study employed Bland–Altman analysis and ROC curve calculations to assess nICP accuracy compared to invasive ICP data.
Results
Successful acquisition of cerebral PPG signals from traumatic brain injury (TBI) patients allowed for the development of a bagging tree model to estimate nICP non-invasively. The nICP estimation exhibited 95% limits of agreement of 3.8 mmHg with minimal bias and a correlation of 0.8254 with invasive ICP monitoring. ROC curve analysis showed strong diagnostic capability with 80% sensitivity and 89% specificity.
Conclusion
The clinical evaluation of this innovative optical nICP sensor revealed its ability to estimate ICP non-invasively with acceptable and clinically useful accuracy. This breakthrough opens the door to further technological refinement and larger-scale clinical studies in the future.
Trial registration
NCT05632302, 11th November 2022, retrospectively registered.
Photoplethysmography (PPG) is an optical noninvasive technique with the potential for assessing tissue perfusion. The relative time-change in the concentration of oxyhemoglobin and deoxyhemoglobin in ...the blood can be derived from DC part of the PPG signal. However, the absolute concentration cannot be determined due to the inadequate data on PPG optical paths. The optical path and differential pathlength factor (DPF) for PPG at red (660 nm) and infrared (880 nm) wavelengths were investigated using a heterogeneous Monte Carlo model of the human forearm. Using the simulated DPFs, the absolute time-change in concentrations were determined from PPG signals recorded from the same tissue site. Results were compared with three conditions of approximated DPFs. Results showed the variation of the optical-path and DPF with different wavelengths and source-detector separations. Approximations resulted in significant errors, for example, using NIRS DPF in PPG led to "cross talk" of −0.4297 and 0.060 and an error of 15.16% to 25.18%. Results confirmed the feasibility of using the PPG (DC) for the assessment of tissue perfusion. The study also identified the inappropriateness of the assumption that DPF is independent of wavelength or source-detector separations and set the platform for further studies on investigating optical pathlengths and DPF in PPG.
Heart rate variability (HRV) is a noninvasive marker of cardiac autonomic activity and has been used in different circumstances to assess the autonomic responses of the body. Pulse rate variability ...(PRV), a similar variable obtained from pulse waves, has been used in recent years as a valid surrogate of HRV. However, the effect that localized changes in autonomic activity have in the relationship between HRV and PRV has not been entirely understood. In this study, a whole-body cold exposure protocol was performed to generate localized changes in autonomic activity, and HRV and PRV from different body sites were obtained. PRV measured from the earlobe and the finger was shown to differ from HRV, and the correlation between these variables was affected by the cold. Also, it was found that PRV from the finger was more affected by cold exposure than PRV from the earlobe. In conclusion, PRV is affected differently to HRV when localized changes in autonomic activity occur. Hence, PRV should not be considered as a valid surrogate of HRV under certain circumstances.Clinical Relevance- This indicates that pulse rate variability is affected differently to heart rate variability when autonomic activity is modified and suggests that pulse rate variability is not always a valid surrogate of heart rate variability
PDF
