Non-invasive Measurement Method Research Articles

Integrated Solution Combining Low-Frequency Forced Oscillation Technique and Continuous Equivital Sensor Monitoring for Assessment of Non-Invasive Ambulatory Respiratory Mechanics

Early assessment of respiratory mechanics is crucial for early-stage diagnosing and managing lung diseases, leading to greater patient outcomes. Traditional methods like spirometry are limited in continuous monitoring and patient compliance as they require forced maneuvers with significant patient cooperation, which may not be available in fragile individuals. The Forced Oscillation Technique (FOT) is a non-invasive measurement method, only based on the tidal breathing at rest from the patient for a limited time period. The proposed solution integrates low-frequency FOT with continuous monitoring using Equivital (EQV) sensors to enhance respiratory mechanics information with heart rate variability. Data were collected over a two-hour period from six healthy volunteers, measuring respiratory impedance every 7 min and continuously recording physiological parameters. The best-fitting fractional-order models for impedance data were identified using genetic algorithms. This study also explores the correlation between impedance model parameters and EQV data, discussing the potential of AI tools for forecasting respiratory properties. Our findings indicate that combined monitoring techniques and AI analysis provides additional complementary information, subsequently aiding the improved evaluation of respiratory function and tissue mechanics. The proposed protocol allows for ambulatory assessment and can be easily performed in normal breathing conditions.

Development of a non-invasive heart rate measurement method for sea turtles with dense keratinous scutes through effective electrode placement

Measuring the heart rate of sea turtles is important for understanding their physiological adaptations to the environment. Non-invasive methods to measure the electrocardiogram (ECG) of sea turtles have been developed by attaching electrodes to their carapace. However, this method has only been applicable to sea turtles with sparse keratin on their shell surfaces, such as loggerhead turtles, and it is difficult to detect heartbeats in sea turtles with dense keratinous scutes, including green sea turtles. Here, we explored the electrode placements on the plastron that can be applied to ECG measurement in green turtles. ECG signals were checked using a handheld ECG monitor at three sets of electrode placement on the plastron. When ECG signals could be detected, they were measured in the water tanks for several days to confirm the clarity of the ECG signals. Of the 29 green turtles, when the negative electrode was placed near the neck area of the plastron, clear ECG signals were obtained in nine individuals (39.1%), whereas ECG signals were not detected at any placements in four individuals (17.4%). Furthermore, in the water tank experiments, continuous ECG signals were successfully recorded by attaching a negative electrode near the neck: almost noiseless clear ECG signals even during moving in seven out of ten individuals and slightly weak and noisy signals in other individuals. The measured heart rate of ten individuals during resting was 8.6 ± 2.9 (means ± s.d.) beats min−1 and that during moving was 12.2 ± 4.7 beats min−1, similar to those reported in a previous study involving the insertion of electrodes inside the body. Therefore, for measuring the ECG of green turtles, the negative electrode should be placed closer to the neck, and the positive and earth electrodes should be placed to the lower left of the plastron. Although the selection of suitable individuals for measurements is required, this heart rate measurement method will contribute to a better understanding of the physiological status of sea turtles with dense keratinous scutes, including green turtles.

Validation of a non-invasive filling pressure (NIFP) device for measuring cardiac pressure and assessing congestion levels in patients with heart failure.

Heart failure (HF) is a high-burden clinical syndrome characterized by intravascular and extravascular congestion, impacting patients' outcomes. Current diagnostic methods for assessing intravascular congestion, including right heart catheterization (RHC), have some limitations. There is a need for accurate, stable, and widely applicable non-invasive measurement methods to improve HF diagnosis and treatment. We conducted non-invasive filling pressure (NIFP) measurements in 74 patients before or after RHC. The correlation between recorded factors and pulmonary arterial wedge pressure (PAWP) values was examined. We tested NIFP's performance as a predictive tool for PAWP using different thresholds. Receiver operating characteristic (ROC) curve analysis and Pearson correlation coefficient were used for data analysis. NIFP measurement served as an independent impact factor and showed a definite relationship with PAWP in both univariate and multivariate regression analyses (all p < 0.05). NIFP demonstrated moderate accuracy in predicting PAWP values (all AUC > 0.75), particularly among patients without arrhythmia [AUC for Model 1 (PAWP >15): 0.80; AUC for Model 2 (PAWP >18): 0.85]. The NIFP device represents a promising innovation, offering non-invasive and user-friendly solution for precisely measuring pulmonary arterial wedge pressure (PAWP) and assessing the degree of congestion.

An Automated Semantic Segmentation Methodology for Infrared Thermography Analysis of the Human Hand

Infrared thermography is a non-invasive measurement method that can accurately describe immediate temperature changes of an object. In the case of continuous in vivo hand measurements, extracting correct thermal data requires a first step of image segmentation to identify regions of interest. This step can be difficult due to parasitic hand movements. It is therefore necessary to regularly readjust the segmented areas throughout the recording. This process is time-consuming and presents a particular obstacle to studying a large number of areas of the hand and long duration sequences. In this work, we propose an automated segmentation methodology that can automatically detect these regions on the hand. This method differs from previous literature because it uses a secondary visual camera and a combination of computer vision and machine learning feature identification. The obtained segmentation models were compared to models segmented by two human operators via Dice and Intersection-over-Union coefficients. The results obtained are very positive: we were able to decompose the images acquired via IRT with our developed algorithms, regardless of the temperature variation, and this with processing times of less than a second. Thus, this technology can be used to study the long-term thermal kinetics of the human hand by automatic feature detection, even in situations where the hand temperature experiences a significant variation.

A High-Precision Real-Time Temperature Acquisition Method Based on Magnetic Nanoparticles.

The unique magnetothermal properties of magnetic nanoparticles enable the development of a high-precision, real-time, noninvasive temperature measurement method with significant potential in the biomedical field. Based on a low-frequency alternating magnetic field excitation model, we construct two additional magnetic field excitation models-alternating current-direct current superposition and dual-frequency superposition-to extract harmonic amplitude components from the magnetization response. To increase the accuracy of harmonic information acquisition, the effects of the truncation error, excitation magnetic field frequency, and amplitude are thoroughly analyzed, and optimal parameter values are selected to minimize the error. A single algorithm is designed for temperature inversion, and a joint algorithm is proposed to optimize the performance of the single algorithm. Under low-frequency alternating-current magnetic field excitation, the autonomous group particle swarm optimization method achieves superior real-time performance in terms of temperature inversion and running time. Compared with the opposition learning gray wolf optimizer and particle swarm optimization-gray wolf optimization, the proposed method achieves reductions of 52% and 68%, respectively. Additionally, under dual-frequency superimposed magnetic field excitation, a higher temperature inversion accuracy is achieved compared with that of the particle swarm optimization-gray wolf optimization algorithm, reducing the error from 0.237 K to 0.094 K.

Heart rate variability and cytokines are involved in anxiety in breast cancer patients: a cross-sectional study

ObjectiveTo explore the correlation between heart rate variability (HRV), peripheral cytokines, anxiety and pain scores in patients with breast cancer (BC). MethodsWe collected blood samples from 100 BC patients and measured the concentrations of Interleukin 6 (IL-6), Interleukin 4 (IL-4) and Interferon gamma (IFN-γ). We collected the patients' 5-minute dynamic electrocardiograms and evaluated their anxiety and pain levels through the Anxiety Self-Rating Scale and the Short-Form McGill Pain Questionnaire (SF-MPQ) Scale. ResultsCompared with patients in the high HRV group, the low HRV group had lower IL-4 levels and higher IFN-γ/IL-4 concentrations. At the same time, the level of anxiety was also higher, but there was no significant difference in pain. Spearman correlation analysis showed that the normal-to-normal cardiac intervals (SDNN), the square root of the mean of the sum of the squares of differences between adjacent normal-to-normal cardiac intervals (RMSSD), high frequency -HRV (HF-HRV) and IL-4 were positively correlated, SDNN and RMSSD were negatively correlated with IFN-γ/IL-4. HRV is negatively correlated with anxiety. Higher SDNN predicts higher IL-4 levels. ConclusionOur results indicate that BC patients with low HRV are associated with higher levels of inflammation and anxiety. Therefore, the measurement of HRV may serve as an objective and non-invasive measurement method for monitoring the immune system and anxiety problems of BC patients. Micro abstractTo explore the correlation between heart rate variability (HRV) and peripheral cytokines, anxiety and pain scores in breast cancer (BC) patients, 116 breast cancer patients were collected for cross-sectional study. We found that BC patients with low HRV were associated with higher levels of inflammation and anxiety. Therefore, the measurement of HRV may serve as an objective and non-invasive measurement method for monitoring the immune system and psychological disorders of BC patients.

Artificial intelligence for brain disease diagnosis using electroencephalogram signals.

Brain signals refer to electrical signals or metabolic changes that occur as a consequence of brain cell activity. Among the various non-invasive measurement methods, electroencephalogram (EEG) stands out as a widely employed technique, providing valuable insights into brain patterns. The deviations observed in EEG reading serve as indicators of abnormal brain activity, which is associated with neurological diseases. Brain‒computer interface (BCI) systems enable the direct extraction and transmission of information from the human brain, facilitating interaction with external devices. Notably, the emergence of artificial intelligence (AI) has had a profound impact on the enhancement of precision and accuracy in BCI technology, thereby broadening the scope of research in this field. AI techniques, encompassing machine learning (ML) and deep learning (DL) models, have demonstrated remarkable success in classifying and predicting various brain diseases. This comprehensive review investigates the application of AI in EEG-based brain disease diagnosis, highlighting advancements in AI algorithms.

Comparison of Frequently Used Fever Measurement Methods: Which One is the Best?

Abstract Objective Peripheral measurement sites and methods used to determine core body temperature were investigated, as there is still debate about which noninvasive core body temperature measurement method is the most valuable and accurate for each age group. Methods Children aged 1 to 36 months were included in the study. The temperature was measured from the forehead (noncontact cutaneous), temporal artery (TA), axilla, and rectum. The rectal measurement was accepted as the reference measurement. A rectal temperature of ≥38.3°C was defined as fever. Results The noncontact cutaneous, axillary, and TA measurements were 1.2, 1.1, and 0.7°C lower than rectal measurements, respectively (p &lt; 0.001, &lt;0.001, &lt;0.001). The TA and noncontact cutaneous measurements demonstrated a moderate positive correlation with rectal measurements, whereas a strong positive correlation was seen between the axillary and rectal measurements. A cutaneous temperature of 37.8°C was found to have a positive predictive value (PPV) of 100%, negative predictive value (NPV) of 81%, sensitivity of 34%, and specificity of 100% for detecting fever. The respective values were 80, 79.4, 23.5, and 98% for an axillary temperature of 37.5°C, and 90, 86.2, 52.9, and 98% for a TA temperature of 38°C. Conclusion The commonly used fever measurement methods have high PPV and NPV and specificity but low sensitivity.

Intraoperative hypotension in children-Measurement and treatment

Intraoperative hypotension is acommon perioperative complication in pediatric anesthesia. Oscillometric blood pressure measurement is therefore an essential part of standard perioperative monitoring in pediatric anesthesia. The optimum measurement site is the upper arm. Attention must be paid to the correct cuff size. Blood pressure should be measured before induction. In children undergoing major surgery or in critically ill children, invasive blood pressure measurement is still the gold standard. Continuous noninvasive measurement methods could be an alternative in the future.Threshold values to define hypotension remain unknown, even in awake children. There are also little data on hypotension thresholds in the perioperative setting. The most reliable measurement parameter for estimating hypotension is the mean arterial pressure. The threshold values for intraoperative hypotension are 40 mm Hg in newborns, 45 mm Hg in infants, 50 mm Hg in young children and 65 mm Hg in adolescents. Treatment should be initiated at adeviation of 10% and intensified at adeviation of 20%.Bolus administration of isotonic balanced crystalloid solutions, vasopressors and/or catecholamines are used as treatment options. Consistent and rapid intervention in the event of hypotension appears to be crucial. So far there is no evidence as to whether this leads to an improvement in outcome parameters.

Development of a unified framework of low-rank approximation and deep neural networks for predicting the spatial variability of SSC in `Spania' watermelons using vis/NIR hyperspectral imaging

Soluble Solids Content (SSC) is an important quality attribute that represents the internal quality of fruits. Visible and near-infrared (Vis/NIR) combined with chemometric algorithms are now popular methods for non-invasive measurement and visualization of SSC. However, in fruits with a thick rind and a large flesh volume, such as watermelon, SSC is not evenly distributed across the fruit. The variability in SSC across the fruit flesh may have an adverse effect on the accuracy of quality analysis algorithms. Thus, this paper presents an accurate and efficient approach for predicting the spatial variation of SSC in watermelons using a combined framework of low-rank approximation and deep neural networks. Watermelon ‘Spania’ was selected for this study, and hyperspectral images of each watermelon were taken from various views, including the top, bottom, and two lateral views. The low-rank property is employed as a constraint in this approach to eliminate the unwanted variations in the spectral data. The low-rank component of the spectral data, free of unwanted variations, is then fed into a fully connected neural network (FNN) for the prediction of watermelon SSC values. The proposed approach obtained optimal performance in calibration and prediction with RC2=0.982, RMSEP = 0.132, and RP2=0.945, RMSEP = 0.195 respectively. Further, the prediction outcomes of the proposed method were compared with state-of-the-art such as Partial Least Square Regression (PLSR), Support Vector Regression (SVR), Multiple Linear Regression (MLR), Decision Tree (DT), and Random Forest (RF). The overall results showed that combining HSI data with a low-rank and deep neural network framework is an efficient method for accurately predicting SSC in watermelons as well as correctly predicting spatial variability of SSC in individual fruits.

Photoacoustic thermal-strain measurement towards noninvasive and accurate temperature mapping in photothermal therapy

Photothermal therapy is a promising tumor treatment approach that selectively eliminates cancer cells while assuring the survival of normal cells. It transforms light energy into thermal energy, making it gentle, targeted, and devoid of radiation. However, the efficacy of treatment is hampered by the absence of accurate and noninvasive temperature measurement method in the therapy. Therefore, there is a pressing demand for a noninvasive temperature measurement method that is real-time and accurate. This article presents one such attempt based on thermal strain photoacoustic (PA) temperature measurement. The method was first modelled, and a circular array-based photoacoustic photothermal system was developed. Experiments with Indian ink as tumor simulants suggest that the temperature monitoring in this work achieves a precision of down to 0.3 °C. Furthermore, it is possible to accomplish real-time temperature imaging, providing accurate two-dimensional temperature mapping for photothermal therapy. Experiments were also conducted on human fingers and nude mice, validating promising potentials of the proposed method for practical implementations.

A non-invasive pipeline heat flux measurement method and application based on CFBG

A non-invasive, real-time monitoring, spectral analysis heat flux sensor with single measuring point based on chirp fiber Bragg grating (CFBG) has been proposed in this paper. When CFBG senses heat flux, the linear increase of axial thermal expansion leads to spectral broadening. The measurement of heat flux can be realized by the measurement of the full width at half maximum (FWHM). The theoretical model and working principle of CFBG heat flux sensor are established to determine the heat flux sensing characteristics of CFBG. The numerical analysis and theoretical calculation show that CFBG heat flux sensor can realize stable transformation of heat flux and FWHM. A heat flux calibration platform was built and its feasibility was verified by simulation. The sensitivity of CFBG sensor to monitor heat flux in a wide temperature range is 1.078 pm/(W/m2). The heat flux of the pipe wall at the outlet of the axial variable piston pump in the hydraulic system was quantitatively measured by the CFBG heat flux sensor. The sensor has a spatial resolution of 1 cm, a length of 10 mm, a diameter of 0.125 mm, and a sensitivity of 1.078 pm/(W/m2). It has the advantages of high spatial resolution, single measurement point, real-time measurement, small installation space, and non-invasiveness. The theoretical model can provide theoretical guidance for the design of fiber grating heat flux sensor, and it is convenient to design a series of sensors for specific measurement requirements.

Applying optical coherence tomography to inline quality monitoring of unidirectional glass-fiber-reinforced thermoplastic tapes

Originally developed for biomedical applications and diagnosis, optical coherence tomography (OCT) has recently been demonstrated to be a powerful non-destructive and non-invasive measurement method for detecting defects in glass-fiber reinforced polymer composites. While previous studies have focused mainly on the use of OCT in the analysis of thermoset composites, we were able to show in offline experiments that OCT can be used to quickly detect typical defects (e.g., dry fiber regions, gaps and fiber breakage) in thermoplastic unidirectional (UD) tapes at high resolution. To investigate the applicability of OCT to inline monitoring, we advanced our previously published approach in two major steps: First, we incorporated the OCT system into an industrial-scale UD-tape production line, and derived optimal settings for inline detection of dry region defects from a comprehensive design of experiments (DoE) to find an optimal balance between accuracy and data size for a stationary tape sample by varying A-scan sampling rate, A-scan averaging and OCT transverse travel velocity. Second, using these optimal settings, we went on to investigate moving tapes over a range of industrially relevant take-off speeds. Microscopy was used for validation in both cases. We developed a fast and robust statistical analysis of B-scans that visualizes the quality of full cross-sections in an interpretable manner for potential use in a real-time setting. Within an industrially relevant production speed range of up to 15 m/min, we are thus now able to investigate 120 mm wide (and potentially wider) UD tapes inline at a transverse resolution of 22 µm, producing only 21 MB of data per measurement.

Experimental study of the wall particle motion in a screw reactor

Screw reactors are gas/solid systems widely employed in industrial applications. Understanding the local powder mixing within these reactors is crucial, particularly at the reactor wall where wall/solid heat transfer occurs. This study proposes a non-invasive measurement method utilizing optical devices to assess wall particle motion. Two techniques for evaluating the particle motion are compared: a simple visual tracking method and particle image velocimetry. Both methods yield similar results, demonstrating consistent wall particle motion across the tube periphery during experimentation. The influence of operational and geometric parameters has been investigated, revealing that filling degree, powder flowability, and screw geometry significantly impact wall particle motion. Symbolic regression has been employed to derive dimensionless models that effectively predict experimental data. These models can be utilized to forecast wall particle motion, serving as a valuable tool for screw conveyor design.

266 nm Laser-Induced Fluorescence Reference Spectra of Ketones and Aromatic Compounds

ABSTRACT Laser-induced fluorescence (LIF) is an established noninvasive measurement method to determine temperature distributions and local gas concentrations in combustion processes with high spatial and temporal resolution. This work presents high-precision LIF spectra of acetone and other tracers at ambient conditions. By using a large UV-sensitive sCMOS camera instead of an image intensified camera, many issues like nonlinearity, varying sensitivity, vignetting, limited resolution etc. could be minimized or eliminated. Particular care was taken to remove residual stray light and to calibrate the spectra with metrological traceability to the International System of Units SI.

A digital volume pulse device-finger photo pulse plethysmography to trace the vascular integrity amongst the low back pain subjects with lumbar disc degenerative diseases diagnosed by MRI analysis.

Finger photo pulse plethysmography is a simple, inexpensive and non-invasive method for measurement of arterial stiffness. The objective is to assess the correlation of arterial stiffness in low back pain subjects with lumbar disc degeneration. Thirty-four back pain patients of both sexes in age group of 30-65 were included. Anthropometric measures like height, body weight, body mass index (BMI) were included. Stiffness index (SI) and reflection index (RI) were measured from the digital volume pulse waveform. There was a negative correlation between SI/RI and no correlation between SI and RI with BMI in both sexes. A significant correlation found between weight and BMI in both sexes. Arterial stiffness may not have any influence on disc degeneration. BMI showed some influence on disc degeneration and back pain.

The Current State of Non-Invasive Measurement of Intracranial Pressure in Patients with Craniosynostosis: A Systematic Review

Introduction: Despite being invasive, direct measurements remain the gold standard to measure intra-cranial pressure (ICP) in patients with craniosynostosis. However, there has been persistent effort to develop non-invasive modalities to measure ICP, possibly avoiding some of the risks of direct measurements. Here, we conduct a systematic review of the evidence behind various non-invasive modalities to monitor ICP in patients with craniosynostosis. Methods: A systematic review was conducted using PubMed, Cochrane, and Web of Science databases to identify studies describing the use of non-invasive ICP measurements in patients with craniosynostosis. Studies were included if they assessed a non-invasive method of ICP monitoring against a direct/invasive ICP monitoring technique in patients with craniosynostosis. Non-English and non-human studies were excluded. Results: A total of 735 studies were screened, of which 52 were included in the study. Nine methods of non-invasive ICP measurement were identified, with varying sensitivities and specificities in detecting elevated ICP. Specifically, optical coherence tomography (OCT), and ocular ultrasonography demonstrated ability to accurately measure ICP when compared to direct measurements. Conclusion: Here, we present the first systemic-review of the current literature surrounding non-invasive modalities to measure ICP in patients with craniosynostosis. While direct measurement remains the gold-standard, multiple reviewed modalities have shown promise in accurately measuring ICP. Of these, OCT has the most rigorous evidence supporting its use. Ocular sonography has also shown promise, albeit without as robust evidence supporting its use. Regardless, further investigation is required before any modality is able to obviate the need for invasive, direct measurements.

Evaluation of agreement between a noninvasive method for real-time measurement of critical blood values with a standard point-of-care device.

The purpose of this work was to investigate the degree of agreement between two distinct approaches for measuring a set of blood values and to compare comfort levels reported by participants when utilizing these two disparate measurement methods. Radial arterial blood was collected for the comparator analysis using the Abbott i-STAT® POCT device. In contrast, the non-invasive proprietary DBC methodology is used to calculate sodium, potassium, chloride, ionized calcium, total carbon dioxide, pH, bicarbonate, and oxygen saturation using four input parameters (temperature, hemoglobin, pO2, and pCO2). Agreement between the measurement for a set of blood values obtained using i-STAT and DBC methodology was compared using intraclass correlation coefficients, Passing and Bablok regression analyses, and Bland Altman plots. A p-value of <0.05 was considered statistically significant. A total of 37 participants were included in this study. The mean age of the participants was 42.4 ± 13 years, most were male (65%), predominantly Caucasian/White (75%), and of Hispanic ethnicity (40%). The Intraclass Correlation Coefficients (ICC) analyses indicated agreement levels ranging from poor to moderate between i-STAT and the DBC's algorithm for Hb, pCO2, HCO3, TCO2, and Na, and weak agreement for pO2, HSO2, pH, K, Ca, and Cl. The Passing and Bablok regression analyses demonstrated that values for Hb, pO2, pCO2, TCO2, Cl, and Na obtained from the i-STAT did not differ significantly from that of the DBC's algorithm suggesting good agreement. The values for Hb, K, and Na measured by the DBC algorithm were slightly higher than those obtained by the i-STAT, indicating some systematic differences between these two methods on Bland Altman Plots. The non-invasive DBC methodology was found to be reliable and robust for most of the measured blood values compared to invasive POCT i-STAT device in healthy participants. These findings need further validation in larger samples and among individuals afflicted with various medical conditions.

Non-invasive temperature monitoring in fixed-bed reactors by electrical capacitance tomography

Abstract Knowledge of the temperature distribution in fixed-bed reactors is of great importance for process control and optimization in many processes of the chemical industry. The state of the art is defined by invasive measuring methods for temperature measurement in such reactors. However, all invasive methods influence both the structure of the fixed-bed and the flow conditions and thus falsify the measurement results compared to real undisturbed conditions in a fixed-bed, above all with regard to the radial temperature profile. In addition, the temperature distribution in the entire reactor is usually derived from a few discrete measuring points based on a model, which sometimes results in large deviations from reality. In this article, electrical capacitance tomography (ECT) is explored as an alternative, non-invasive measurement method to monitor the temperature distribution inside fixed-bed reactors. The method exploits the temperature dependence of the effective bulk permittivity of the reactor filling. By way of an example, this dependence has been investigated in this work for two different hydrogenation catalysts. A temperature-resistant ECT sensor has been designed to perform measurements under the influence of temperature. The investigations show that, with the aid of ECT, it is possible to detect relative temperature changes in the region of interest with the materials examined.

Validation of oscillometric ratio and maximum gradient methods for non-invasive blood pressure measurement with intra-arterial blood pressure measurements as reference.

Most non-invasive blood pressure (BP) measurements are carried out using instruments which implement either the Ratio or the Maximum Gradient oscillometric method, mostly during cuff deflation, but more rarely during cuff inflation. Yet, there is little published literature on the relative advantages and accuracy of these two methods. In this study of 40 lightly sedated individuals aged 64.1 ± 9.6 years, we evaluate and compare the performance of the oscillometric ratio (K) and gradient (Grad) methods for the non-invasive estimation of mean pressure, SBP and DBP with reference to invasive intra-arterial values. There was no significant difference between intra-arterial estimates of mean pressure made via Korotkoff sounds (MP-OWE) or the gradient method (MP-Grad). However, 17.7% of MP-OWE and 15% of MP-Grad were in error by more than 10 mmHg. SBP-K and SBP-Grad underestimated SBP by 14 and 18 mmHg, whilst accurately estimating DBP with mean errors of 0.4 ± 5.0 and 1.7 ± 6.1 mmHg, respectively. Relative to the reference standard SBP-K, SBP-Grad and DBP-Grad were estimated with a mean error of -4.5 ± 6.6 and 1.4 ± 5.6 mmHg, respectively, noting that using the full range of recommended ratios introduces errors of 12 and 7 mmHg in SBP and DBP, respectively. We also show that it is possible to find ratios which minimize the root mean square error (RMSE) and the mean error for any particular individual cohort. We developed linear models for estimating SBP and SBP-K from a range of demographic and non-invasive OWE variables with resulting mean errors of 0.15 ± 5.6 and 0.3 ± 5.7 mmHg, acceptable according to the Universal standard.