The Feasibility of Semi-Continuous and Multi-Frequency Thoracic Bioimpedance Measurements by a Wearable Device during Fluid Changes in Hemodialysis Patients.

Repeated single-point measurements of thoracic bioimpedance at a single (low) frequency are strongly related to fluid changes during hemodialysis. Extension to semi-continuous measurements may provide longitudinal details in the time pattern of the bioimpedance signal, and multi-frequency measurements may add in-depth information on the distribution between intra- and extracellular fluid. This study aimed to investigate the feasibility of semi-continuous multi-frequency thoracic bioimpedance measurements by a wearable device in hemodialysis patients. Therefore, thoracic bioimpedance was recorded semi-continuously (i.e., every ten minutes) at nine frequencies (8-160 kHz) in 68 patients during two consecutive hemodialysis sessions, complemented by a single-point measurement at home in-between both sessions. On average, the resistance signals increased during both hemodialysis sessions and decreased during the interdialytic interval. The increase during dialysis was larger at 8 kHz (∆ 32.6 Ω during session 1 and ∆ 10 Ω during session 2), compared to 160 kHz (∆ 29.5 Ω during session 1 and ∆ 5.1 Ω during session 2). Whereas the resistance at 8 kHz showed a linear time pattern, the evolution of the resistance at 160 kHz was significantly different (p < 0.0001). Measuring bioimpedance semi-continuously and with a multi-frequency current is a major step forward in the understanding of fluid dynamics in hemodialysis patients. This study paves the road towards remote fluid monitoring.

Exploring the perception of stress in childhood and early adolescence.

Stressful life experiences may jeopardize the healthy development of children. To improve interventions, more knowledge is needed on the perception of stress by children. In adults, stress is regarded as a state of low valence and high arousal. It is unclear whether children perceive stress similarly. In the current study, 35 children of the general population completed three tasks aiming to provide insight into their knowledge of the concept stress. In the first task, participants were asked about their verbal knowledge of the concept stress. In the second task, they rated the valence and arousal of eight emotion-evoking vignettes. In the final task, participants completed an experience sampling survey for at least 1 day, consisting of a stress thermometer and pictorial scales of valence and arousal. Participants' perception of stress was found to be mainly valence focused. Age and sex were found to play a role in the degree of arousal focus. Older participants differentiated more in arousal levels than younger participants, as did girls in comparison with boys. Because the perception of stress depends on developmental and other individual factors, using stress as a single measurement dimension in a survey is not recommended.

Comparison between Speckle Plethysmography and Photoplethysmography during Cold Pressor Test Referenced to Finger Arterial Pressure.

Speckle Plethysmography (SPG) and Photoplethysmography (PPG) are different biophotonics technologies that allow for measurement of haemodynamics. As the difference between SPG and PPG under low perfusion conditions is not fully understood, a Cold Pressor Test (CPT-60 s full hand immersion in ice water), was used to modulate blood pressure and peripheral circulation. A custom-built setup simultaneously derived SPG and PPG from the same video streams at two wavelengths (639 nm and 850 nm). SPG and PPG were measured at the right index finger location before and during the CPT using finger Arterial Pressure (fiAP) as a reference. The effect of the CPT on the Alternating Component amplitude (AC) and Signal-to-Noise Ratio (SNR) of dual-wavelength SPG and PPG signals was analysed across participants. Furthermore, waveform differences between SPG, PPG, and fiAP based on frequency harmonic ratios were analysed for each subject (n = 10). Both PPG and SPG at 850 nm show a significant reduction during the CPT in both AC and SNR. However, SPG showed significantly higher and more stable SNR than PPG in both study phases. Harmonic ratios were found substantially higher in SPG than PPG. Therefore, in low perfusion conditions, SPG seems to offer a more robust pulse wave monitoring with higher harmonic ratios than PPG.

Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint.

The ability to objectively measure aspects of performance and behavior is a fundamental pillar of digital health, enabling digital wellness products, decentralized trial concepts, evidence generation, digital therapeutics, and more. Emerging multimodal technologies capable of measuring several modalities simultaneously and efforts to integrate inputs across several sources are further expanding the limits of what digital measures can assess. Experts from the field of digital health were convened as part of a multi-stakeholder workshop to examine the progress of multimodal digital measures in two key areas: detection of disease and the measurement of meaningful aspects of health relevant to the quality of life. Here we present a meeting report, summarizing key discussion points, relevant literature, and finally a vision for the immediate future, including how multimodal measures can provide value to stakeholders across drug development and care delivery, as well as three key areas where headway will need to be made if we are to continue to build on the encouraging progress so far: collaboration and data sharing, removal of barriers to data integration, and alignment around robust modular evaluation of new measurement capabilities.

Camera-Derived Photoplethysmography (rPPG) and Speckle Plethysmography (rSPG): Comparing Reflective and Transmissive Mode at Various Integration Times Using LEDs and Lasers.

Background: Although both speckle plethysmography (SPG) and photoplethysmography (PPG) examine pulsatile changes in the vasculature using opto-electronics, PPG has a long history, whereas SPG is relatively new and less explored. The aim of this study was to compare the effects of integration time and light-source coherence on signal quality and waveform morphology for reflective and transmissive rSPG and rPPG. Methods: (A) Using time-domain multiplexing, we illuminated 10 human index fingers with pulsed lasers versus LEDs (both at 639 and 850 nm), in transmissive versus reflective mode. A synchronized camera (Basler acA2000-340 km, 25 cm distance, 200 fps) captured and demultiplexed four video channels (50 fps/channel) in four stages defined by illumination mode. From all video channels, we derived rPPG and rSPG, and applied a signal quality index (SQI, scale: Good > 0.95; Medium 0.95−0.85; Low 0.85−0.8; Negligible < 0.8); (B) For transmission videos only, we additionally calculated the intensity threshold area (ITA), as the area of the imaging exceeding a certain intensity value and used linear regression analysis to understand unexpected similarities between rPPG and rSPG. Results: All mean SQI-values. Reflective mode: Laser-rSPG > 0.965, LED-rSPG < 0.78, rPPG < 0.845. Transmissive mode: 0.853−0.989 for rSPG and rPPG at all illumination settings. Coherent mode: Reflective rSPG > 0.951, reflective rPPG < 0.740, transmissive rSPG and rPPG 0.990−0.898. Incoherent mode: Reflective all <0.798 and transmissive all 0.92−0.987. Linear regressions revealed similar R2 values of rPPG with rSPG (R2 = 0.99) and ITA (R2 = 0.98); Discussion: Laser-rSPG and LED-rPPG produced different waveforms in reflection, but not in transmission. We created the concept of ITA to investigate this behavior. Conclusions: Reflective Laser-SPG truly originated from coherence. Transmissive Laser-rSPG showed a loss of speckles, accompanied by waveform changes towards rPPG. Diffuse spatial intensity modulation polluted spatial-mode SPG.

Performance and limitation estimation of a three-tap gated imaging sensor in wide field time-gated fluorescence lifetime imaging systems.

In this paper, a computational performance analysis is presented of a wide-field time-gated fluorescence lifetime imaging microscope (FLIM) using practically realizable properties of the laser, sample, and a three-tap time-gated CMOS image sensor. The impact of these component-level properties on the accuracy and the precision of the measurement results are estimated and discussed based on Monte Carlo simulations. The correlation between the detector speed and the accuracy of the extracted fluorescence lifetime is studied, and the minimum required incident photoelectron number of each pixel is estimated for different detector speeds and different fluorescence lifetime measurements. In addition, the detection limits due to the dark current and the parasitic light sensitivity of the detector are also investigated. This work gives an overview of the required fluorescence emission condition as well as the required detector properties for a three-tap time-gated image sensor to achieve good FLIM data in biological applications.

Supervised SVM Transfer Learning for Modality-Specific Artefact Detection in ECG.

The electrocardiogram (ECG) is an important diagnostic tool for identifying cardiac problems. Nowadays, new ways to record ECG signals outside of the hospital are being investigated. A promising technique is capacitively coupled ECG (ccECG), which allows ECG signals to be recorded through insulating materials. However, as the ECG is no longer recorded in a controlled environment, this inevitably implies the presence of more artefacts. Artefact detection algorithms are used to detect and remove these. Typically, the training of a new algorithm requires a lot of ground truth data, which is costly to obtain. As many labelled contact ECG datasets exist, we could avoid the use of labelling new ccECG signals by making use of previous knowledge. Transfer learning can be used for this purpose. Here, we applied transfer learning to optimise the performance of an artefact detection model, trained on contact ECG, towards ccECG. We used ECG recordings from three different datasets, recorded with three recording devices. We showed that the accuracy of a contact-ECG classifier improved between 5 and 8% by means of transfer learning when tested on a ccECG dataset. Furthermore, we showed that only 20 segments of the ccECG dataset are sufficient to significantly increase the accuracy.

Artefact Detection in Impedance Pneumography Signals: A Machine Learning Approach.

Impedance pneumography has been suggested as an ambulatory technique for the monitoring of respiratory diseases. However, its ambulatory nature makes the recordings more prone to noise sources. It is important that such noisy segments are identified and removed, since they could have a huge impact on the performance of data-driven decision support tools. In this study, we investigated the added value of machine learning algorithms to separate clean from noisy bio-impedance signals. We compared three approaches: a heuristic algorithm, a feature-based classification model (SVM) and a convolutional neural network (CNN). The dataset consists of 47 chronic obstructive pulmonary disease patients who performed an inspiratory threshold loading protocol. During this protocol, their respiration was recorded with a bio-impedance device and a spirometer, which served as a gold standard. Four annotators scored the signals for the presence of artefacts, based on the reference signal. We have shown that the accuracy of both machine learning approaches (SVM: 87.77 ± 2.64% and CNN: 87.20 ± 2.78%) is significantly higher, compared to the heuristic approach (84.69 ± 2.32%). Moreover, no significant differences could be observed between the two machine learning approaches. The feature-based and neural network model obtained a respective AUC of 92.77±2.95% and 92.51±1.74%. These findings show that a data-driven approach could be beneficial for the task of artefact detection in respiratory thoracic bio-impedance signals.

Color lens-free imaging using multi-wavelength illumination based phase retrieval.

Accurate image reconstruction in color lens-free imaging has proven challenging. The color image reconstruction of a sample is impacted not only by how strongly the illumination intensity is absorbed at a given spectral range, but also by the lack of phase information recorded on the image sensor. We present a compact and cost-effective approach of addressing the need for phase retrieval to enable robust color image reconstruction in lens-free imaging. The amplitude images obtained at transparent wavelength bands are used to estimate the phase in highly absorbed wavelength bands. The accurate phase information, obtained through our iterative algorithm, removes the color artefacts due to twin-image noise in the reconstructed image and improves image reconstruction quality to allow accurate color reconstruction. This could enable the technique to be applied for imaging of stained pathology slides, an important tool in medical diagnostics.

Thin-film interference filters illuminated by tilted apertures.

Thin-film interference filters can be illuminated by a circular aperture at different angles. Each situation produces a different transmittance spectrum. We present an analytical model that, for small tilt angles, predicts the change in transmittance for an arbitrary position of the filter in three-dimensional space. The model is extended to take into account higher-order harmonics. We also derive a formula to predict the change in central wavelength, and we validate our results by comparison with thin-film transfer-matrix calculations. A key property of our approach is that the model can be combined with empirical data to predict the transmittance without knowing the filter design.

Towards personalized fluid monitoring in haemodialysis patients: thoracic bioimpedance signal shows strong correlation with fluid changes, a cohort study.

BACKGROUND: Haemodialysis (HD) patients are burdened by frequent fluid shifts which amplify their comorbidities. Bioimpedance (bioZ) is a promising technique to monitor changes in fluid status. The aim of this study is to investigate if the thoracic bioZ signal can track fluid changes during a HD session. METHODS: Prevalent patients from a single centre HD unit were monitored during one to six consecutive HD sessions using a wearable multi-frequency thoracic bioZ device. Ultrafiltration volume (UFV) was determined based on the interdialytic weight gain and target dry weight set by clinicians. The correlation between the bioZ signal and UFV was analysed on population level. Additionally regression models were built and validated per dialysis session. RESULTS: 66 patients were included, resulting in a total of 133 HD sessions. Spearman correlation between the thoracic bioZ and UFV showed a significant strong correlation of 0.755 (p < 0.01) on population level. Regression analysis per session revealed a strong relation between the bioZ value and the UFV (R2 = 0.982). The fluid extraction prediction error of the leave-one-out cross validation was very small (56.2 ml [- 121.1-194.1 ml]) across all sessions at all frequencies. CONCLUSIONS: This study demonstrated that thoracic bioZ is strongly correlated with fluid shifts during HD over a large range of UFVs. Furthermore, leave-one-out cross validation is a step towards personalized fluid monitoring during HD and could contribute to the creation of autonomous dialysis.

Relationship Between Chronic Stress and Heart Rate Over Time Modulated by Gender in a Cohort of Office Workers: Cross-Sectional Study Using Wearable Technologies.

BACKGROUND: Chronic stress is increasing in prevalence and is associated with several physical and mental disorders. Although it is proven that acute stress changes physiology, much less is known about the relationship between physiology and long-term stress. Continuous measurement of vital signs in daily life and chronic stress detection algorithms could serve this purpose. For this, it is paramount to model the effects of chronic stress on human physiology and include other cofounders, such as demographics, enabling the enrichment of a population-wide approach with individual variations. OBJECTIVE: The main objectives of this study were to investigate the effect of chronic stress on heart rate (HR) over time while correcting for weekdays versus weekends and to test a possible modulation effect by gender and age in a healthy cohort. METHODS: Throughout 2016 and 2017, healthy employees of technology companies were asked to participate in a 5-day observation stress study. They were required to wear two wearables, of which one included an electrocardiogram sensor. The derived HR was averaged per hour and served as an output for a mixed design model including a trigonometric fit over time with four harmonics (periods of 24, 12, 8, and 6 hours), gender, age, whether it was a workday or weekend day, and a chronic stress score derived from the Perceived Stress Scale (PSS) as predictors. RESULTS: The study included 328 subjects, of which 142 were female and 186 were male participants, with a mean age of 38.9 (SD 10.2) years and a mean PSS score of 13.7 (SD 6.0). As main effects, gender (χ21=24.02, P<.001); the hour of the day (χ21=73.22, P<.001); the circadian harmonic (χ22=284.4, P<.001); and the harmonic over 12 hours (χ22=242.1, P<.001), over 8 hours (χ22=23.78, P<.001), and over 6 hours (χ22=82.96, P<.001) had a significant effect on HR. Two three-way interaction effects were found. The interaction of age, whether it was a workday or weekend day, and the circadian harmonic over time were significantly correlated with HR (χ22=7.13, P=.03), as well as the interaction of gender, PSS score, and the circadian harmonic over time (χ22=7.59, P=.02). CONCLUSIONS: The results show a relationship between HR and the three-way interaction of chronic stress, gender, and the circadian harmonic. The modulation by gender might be related to evolution-based energy utilization strategies, as suggested in related literature studies. More research, including daily cortisol assessment, longer recordings, and a wider population, should be performed to confirm this interpretation. This would enable the development of more complete and personalized models of chronic stress.

Using Biosensors and Digital Biomarkers to Assess Response to Cardiac Rehabilitation: Observational Study.

BACKGROUND: Cardiac rehabilitation (CR) is known for its beneficial effects on functional capacity and is a key component within current cardiovascular disease management strategies. In addition, a larger increase in functional capacity is accompanied by better clinical outcomes. However, not all patients respond in a similar way to CR. Therefore, a patient-tailored approach to CR could open up the possibility to achieve an optimal increase in functional capacity in every patient. Before treatment can be optimized, the differences in response of patients in terms of cardiac adaptation to exercise should first be understood. In addition, digital biomarkers to steer CR need to be identified. OBJECTIVE: The aim of the study was to investigate the difference in cardiac response between patients characterized by a clear improvement in functional capacity and patients showing only a minor improvement following CR therapy. METHODS: A total of 129 patients in CR performed a 6-minute walking test (6MWT) at baseline and during four consecutive short-term follow-up tests while being equipped with a wearable electrocardiogram (ECG) device. The 6MWTs were used to evaluate functional capacity. Patients were divided into high- and low-response groups, based on the improvement in functional capacity during the CR program. Commonly used heart rate parameters and cardiac digital biomarkers representative of the heart rate behavior during the 6MWT and their evolution over time were investigated. RESULTS: All participating patients improved in functional capacity throughout the CR program (P<.001). The heart rate parameters, which are commonly used in practice, evolved differently for both groups throughout CR. The peak heart rate (HRpeak) from patients in the high-response group increased significantly throughout CR, while no change was observed in the low-response group (F4,92=8.321, P<.001). Similar results were obtained for the recovery heart rate (HRrec) values, which increased significantly over time during every minute of recuperation, for the high-response group (HRrec1: P<.001, HRrec2: P<.001, HRrec3: P<.001, HRrec4: P<.001, and HRrec5: P=.02). The other digital biomarkers showed that the evolution of heart rate behavior during a standardized activity test differed throughout CR between both groups. These digital biomarkers, derived from the continuous measurements, contribute to more in-depth insight into the progression of patients' cardiac responses. CONCLUSIONS: This study showed that when using wearable sensor technology, the differences in response of patients to CR can be characterized by means of commonly used heart rate parameters and digital biomarkers that are representative of cardiac response to exercise. These digital biomarkers, derived by innovative analysis techniques, allow for more in-depth insights into the cardiac response of cardiac patients during standardized activity. These results open up the possibility to optimized and more patient-tailored treatment strategies and to potentially improve CR outcome.

Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation.

Cardiovascular diseases (CVD) are often characterized by their multifactorial complexity. This makes remote monitoring and ambulatory cardiac rehabilitation (CR) therapy challenging. Current wearable multimodal devices enable remote monitoring. Machine learning (ML) and artificial intelligence (AI) can help in tackling multifaceted datasets. However, for clinical acceptance, easy interpretability of the AI models is crucial. The goal of the present study was to investigate whether a multi-parameter sensor could be used during a standardized activity test to interpret functional capacity in the longitudinal follow-up of CR patients. A total of 129 patients were followed for 3 months during CR using 6-min walking tests (6MWT) equipped with a wearable ECG and accelerometer device. Functional capacity was assessed based on 6MWT distance (6MWD). Linear and nonlinear interpretable models were explored to predict 6MWD. The t-distributed stochastic neighboring embedding (t-SNE) technique was exploited to embed and visualize high dimensional data. The performance of support vector machine (SVM) models, combining different features and using different kernel types, to predict functional capacity was evaluated. The SVM model, using chronotropic response and effort as input features, showed a mean absolute error of 42.8 m (±36.8 m). The 3D-maps derived using the t-SNE technique visualized the relationship between sensor-derived biomarkers and functional capacity, which enables tracking of the evolution of patients throughout the CR program. The current study showed that wearable monitoring combined with interpretable ML can objectively track clinical progression in a CR population. These results pave the road towards ambulatory CR.

Motion Artifact Reduction for Wrist-Worn Photoplethysmograph Sensors Based on Different Wavelengths.

Long-term heart rate (HR) monitoring by wrist-worn photoplethysmograph (PPG) sensors enables the assessment of health conditions during daily life with high user comfort. However, PPG signals are vulnerable to motion artifacts (MAs), which significantly affect the accuracy of estimated physiological parameters such as HR. This paper proposes a novel modular algorithm framework for MA removal based on different wavelengths for wrist-worn PPG sensors. The framework uses a green PPG signal for HR monitoring and an infrared PPG signal as the motion reference. The proposed framework includes four main steps: motion detection, motion removal using continuous wavelet transform, approximate HR estimation and signal reconstruction. The proposed algorithm is evaluated against an electrocardiogram (ECG) in terms of HR error for a dataset of 6 healthy subjects performing 21 types of motion. The proposed MA removal method reduced the average error in HR estimation from 4.3, 3.0 and 3.8 bpm to 0.6, 1.0 and 2.1 bpm in periodic, random, and continuous non-periodic motion situations, respectively.

Finite aperture correction for spectral cameras with integrated thin-film Fabry-Perot filters.

Spectral cameras with integrated thin-film Fabry-Perot filters enable many different applications. Some applications require the detection of spectral features that are only visible at specific wavelengths, and some need to quantify small spectral differences that are undetectable with RGB color cameras. One factor that influences the central wavelength of thin-film filters is the angle of incidence. Therefore, when light is focused from an imaging lens onto the filter array, undesirable shifts in the measured spectra are observed. These shifts limit the use of the sensor in applications that require fast lenses or lenses with large chief ray angles. To increase flexibility and enable new applications, we derive an analytical model that explains and can correct the observed shifts in measured spectra. The model includes the size of the aperture and physical position of each filter on the sensor. We experimentally validate the model with two spectral cameras: one in the visible and near-infrared region and one in the short wave infrared region.

Evaluation of a Multichannel Non-Contact ECG System and Signal Quality Algorithms for Sleep Apnea Detection and Monitoring.

Sleep-related conditions require high-cost and low-comfort diagnosis at the hospital during one night or longer. To overcome this situation, this work aims to evaluate an unobtrusive monitoring technique for sleep apnea. This paper presents, for the first time, the evaluation of contactless capacitively-coupled electrocardiography (ccECG) signals for the extraction of sleep apnea features, together with a comparison of different signal quality indicators. A multichannel ccECG system is used to collect signals from 15 subjects in a sleep environment from different positions. Reference quality labels were assigned for every 30-s segment. Quality indicators were calculated, and their signal classification performance was evaluated. Features for the detection of sleep apnea were extracted from capacitive and reference signals. Sleep apnea features related to heart rate and heart rate variability achieved high similarity to the reference values, with p-values of 0.94 and 0.98, which is in line with the more than 95% beat-matching obtained. Features related to signal morphology presented lower similarity with the reference, although signal similarity metrics of correlation and coherence were relatively high. Quality-based automatic classification of the signals had a maximum accuracy of 91%. Best-performing quality indicators were based on template correlation and beat-detection. Results suggest that using unobtrusive cardiac signals for the automatic detection of sleep apnea can achieve similar performance as contact signals, and indicates clinical value of ccECG. Moreover, signal segments can automatically be classified by the proposed quality metrics as a pre-processing step. Including contactless respiration signals is likely to improve the performance and provide a complete unobtrusive cardiorespiratory monitoring solution; this is a promising alternative that will allow the screening of more patients with higher comfort, for a longer time, and at a reduced cost.

Development of Gated Pinned Avalanche Photodiode Pixels for High-Speed Low-Light Imaging.

This work explores the benefits of linear-mode avalanche photodiodes (APDs) in high-speed CMOS imaging as compared to different approaches present in literature. Analysis of APDs biased below their breakdown voltage employed in single-photon counting mode is also discussed, showing a potentially interesting alternative to existing Geiger-mode APDs. An overview of the recently presented gated pinned avalanche photodiode pixel concept is provided, as well as the first experimental results on a 8 × 16 pixel test array. Full feasibility of the proposed pixel concept is not demonstrated; however, informative data is obtained from the sensor operating under -32 V substrate bias and clearly exhibiting wavelength-dependent gain in frontside illumination. The readout of the chip designed in standard 130 nm CMOS technology shows no dependence on the high-voltage bias. Readout noise level of 15 e - rms, full well capacity of 8000 e - , and the conversion gain of 75 µV / e - are extracted from the photon-transfer measurements. The gain characteristics of the avalanche junction are characterized on separate test diodes showing a multiplication factor of 1.6 for red light in frontside illumination.

Soft, comfortable polymer dry electrodes for high quality ECG and EEG recording.

Conventional gel electrodes are widely used for biopotential measurements, despite important drawbacks such as skin irritation, long set-up time and uncomfortable removal. Recently introduced dry electrodes with rigid metal pins overcome most of these problems; however, their rigidity causes discomfort and pain. This paper presents dry electrodes offering high user comfort, since they are fabricated from EPDM rubber containing various additives for optimum conductivity, flexibility and ease of fabrication. The electrode impedance is measured on phantoms and human skin. After optimization of the polymer composition, the skin-electrode impedance is only ~10 times larger than that of gel electrodes. Therefore, these electrodes are directly capable of recording strong biopotential signals such as ECG while for low-amplitude signals such as EEG, the electrodes need to be coupled with an active circuit. EEG recordings using active polymer electrodes connected to a clinical EEG system show very promising results: alpha waves can be clearly observed when subjects close their eyes, and correlation and coherence analyses reveal high similarity between dry and gel electrode signals. Moreover, all subjects reported that our polymer electrodes did not cause discomfort. Hence, the polymer-based dry electrodes are promising alternatives to either rigid dry electrodes or conventional gel electrodes.

Advancing the Local Pulse Wave Velocity Measurement-Wave Confluence Decomposition Using a Double Gaussian Propagation Model.

Background Pulse wave velocity (PWV) is a marker of arterial stiffness and local measurements could facilitate its widescale clinical use. However, confluence of incident and early reflected waves leads to biased spatiotemporal PWV estimates. Objective We introduce the Double Gaussian Propagation Model (DGPM) to measure local PWV in consideration of wave confluence (PWV[Formula: see text]) and compare it against conventional spatiotemporal PWV (PWV[Formula: see text]), with Bramwell-Hill PWV (PWV[Formula: see text]) and blood pressure (BP) as reference measures. Methods Ten subjects ranging from normotension to hypertension were repeatedly measured at rest and with induced PWV changes. Carotid distension waveforms over a 19 mm wide segment were acquired from ultrasonography, simultaneously with noninvasive continuous BP. Per cardiac cycle, the 8-parameter DGPM (amplitude, centroid, width, and velocity, respectively of forward and backward propagating wave) was fitted to the distension waveforms' systolic foot and dicrotic notch complexes. Corresponding PWV[Formula: see text] was computed from linear fittings of respective feature timings and distances. Regression analyses were conducted with PWV[Formula: see text] and PWV[Formula: see text] as predictors, and various PWV and BP measures as response variables. Results Whereas PWV[Formula: see text] correlations were insignificant, PWV[Formula: see text] estimated the reference PWV[Formula: see text] with a significant reduction in errors (P < 0.001), explained up to 65% PWV[Formula: see text] variability at rest, demonstrated higher intra-method consistency and correlated significantly with all BP measures (P < 0.001). Conclusion The proposed DGPM measures local carotid PWV in consideration of wave confluence, showing significant correlations with Bramwell-Hill PWV and BP at two distinct waveform complexes. Thereby PWV[Formula: see text] outperforms the conventional PWV[Formula: see text] in all investigated respects, potentially enabling PWV assessment in routine clinical practice.