Comparison of different modulations of photoplethysmography in extracting respiratory rate: from a physiological perspective

A Novel Respiratory Rate Estimation Algorithm from Photoplethysmogram Using Deep Learning Model

Respiratory rate (RR) is a critical vital sign that can provide valuable insights into various medical conditions, including pneumonia. Unfortunately, manual RR counting is often unreliable and discontinuous. Current RR estimation algorithms either lack the necessary accuracy or demand extensive window sizes. In response to these challenges, this study introduces a novel method for continuously estimating RR from photoplethysmogram (PPG) with a reduced window size and lower processing requirements. To evaluate and compare classical and deep learning algorithms, this study leverages the BIDMC and CapnoBase datasets, employing the Respiratory Rate Estimation (RRest) toolbox. The optimal classical techniques combination on the BIDMC datasets achieves a mean absolute error (MAE) of 1.9 breaths/min. Additionally, the developed neural network model utilises convolutional and long short-term memory layers to estimate RR effectively. The best-performing model, with a 50% train-test split and a window size of 7 s, achieves an MAE of 2 breaths/min. Furthermore, compared to other deep learning algorithms with window sizes of 16, 32, and 64 s, this study's model demonstrates superior performance with a smaller window size. The study suggests that further research into more precise signal processing techniques may enhance RR estimation from PPG signals.

Predictors of Nocturnal Hypoxemic Burden in Patients Undergoing Elective Coronary Artery Bypass Grafting Surgery

Background: Nocturnal hypoxemia has been linked to increased cardiovascular morbidity and mortality. Several common diseases, such as sleep-disordered breathing (SDB), heart failure (HF), obesity, and pulmonary disease, coincide with an elevated nocturnal hypoxemic burden with and without repetitive desaturations. Research question: This study aimed to evaluate the association of relevant common diseases with distinctive metrics of nocturnal hypoxemic burden with and without repetitive desaturations in patients undergoing coronary artery bypass grafting surgery. Study design and methods: In this subanalysis of the prospective observational study, CONSIDER-AF (NCT02877745) portable SDB monitoring was performed on 429 patients with severe coronary artery disease the night before cardiac surgery. Pulse oximetry was used to determine nocturnal hypoxemic burden, as defined by total recording time spent with oxygen saturation levels < 90% (T90). T90 was further characterized as T90 due to intermittent hypoxemia (T90desaturation) and T90 due to nonspecific and noncyclic SpO2-drifts (T90non-specific). Results: Multivariable linear regression analysis identified SDB (apnea-hypopnea-index ≥ 15/h; B [95% CI]: 6.5 [0.4; 12.5], p = 0.036), obesity (8.2 [2.5; 13.9], p = 0.005), and mild-to-moderate chronic obstructive pulmonary disease (COPD, 16.7 [8.5; 25.0], p < 0.001) as significant predictors of an increased nocturnal hypoxemic burden. Diseases such as SDB, obesity and HF were significantly associated with elevated T90desaturation. In contrast, obesity and mild-to-moderate COPD were significant modulators of T90non-specific. Interpretation: SDB and leading causes for SDB, such as obesity and HF, are associated with an increased nocturnal hypoxemic burden with repetitive desaturations. Potential causes for hypoventilation syndromes, such as obesity and mild-to-moderate COPD, are linked to an increased hypoxemic burden without repetitive desaturations. Clinical Trial Registration: ClinicalTrials.gov identifier: NCT02877745.

On the cardiorespiratory coordination assessed by the photoplethysmography imaging technique

Cardiorespiratory coordination (CRC) probes the interaction between cardiac and respiratory oscillators in which cardiac and respiratory activity are synchronized, with individual heartbeats occurring at approximately the same temporal positions during several breathing cycles. An increase of CRC has previously been related to pathological stressful states. We studied CRC employing coordigrams computed from non-contact photoplethysmography imaging (PPGI) and respiratory data using the optical flow method. In a blocked study design, we applied the cold pressure test (CPT), water at ambient temperature (AWT), and intermittent resting conditions. In controls (no intervention), CRC remained on initial low levels throughout measurements. In the experimental group (AWT and CPT intervention), CRC decreased during AWT and CPT. Following both interventions, CRC increased significantly, with a rebound effect following AWT. In controls, HR increased steadily over time. CPT evoked a significant HR increase which correlated with subjective stress/pain ratings. The CRC increase following AWT correlated significantly with subjective pain (r = .79) and stress (r = .63) ratings. Furthermore, we observed a significant correlation (r = - .80) between mean RMSSD and mean duration of CRC, which further supports an association between autonomic state and CRC level. CRC analysis obtained from cutaneous tissue perfusion data therefore appears to be a sensitive and useful method for the study of CRC and ANS activity. Future studies need to investigate the physiological principles and clinical significance of these findings.

Contactless photoplethysmography for assessment of small fiber neuropathy

Chronic pain is a prevalent condition affecting approximately one-fifth of the global population, with significant impacts on quality of life and work productivity. Small fiber neuropathies are a common cause of chronic pain, and current diagnostic methods rely on subjective self-assessment or invasive skin biopsies, highlighting the need for objective noninvasive assessment methods. The study aims to develop a modular prototype of a contactless photoplethysmography system with three spectral bands (420, 540, and 800 nm) and evaluate its potential for assessing peripheral neuropathy patients via a skin topical heating test and spectral analyses of cutaneous flowmotions. The foot topical skin heating test was conducted on thirty volunteers, including fifteen healthy subjects and fifteen neuropathic patients. Four cutaneous nerve fiber characterizing parameters were evaluated at different wavelengths, including vasomotor response trend, flare area, flare intensity index, and the spectral power of cutaneous flowmotions. The results show that neuropathic patients had significantly lower vasomotor response (50%), flare area (63%), flare intensity index (19%), and neurogenic component (54%) of cutaneous flowmotions compared to the control group, independent of photoplethysmography spectral band. An absolute value of perfusion was 20%-30% higher in the 420 nm band. Imaging photoplethysmography shows potential as a cost-effective alternative for objective and non-invasive assessment of neuropathic patients, but further research is needed to enhance photoplethysmography signal quality and establish diagnostic criteria.

Filtering-induced changes of pulse transmit time across different ages: a neglected concern in photoplethysmography-based cuffless blood pressure measurement

Background: Pulse transit time (PTT) is a key parameter in cuffless blood pressure measurement based on photoplethysmography (PPG) signals. In wearable PPG sensors, raw PPG signals are filtered, which can change the timing of PPG waveform feature points, leading to inaccurate PTT estimation. There is a lack of comprehensive investigation of filtering-induced PTT changes in subjects with different ages. Objective: This study aimed to quantitatively investigate the effects of aging and PTT definition on the infinite impulse response (IIR) filtering-induced PTT changes. Methods: One hundred healthy subjects in five different ranges of age (i.e., 20-29, 30-39, 40-49, 50-59, and over 60 years old, 20 subjects in each) were recruited. Electrocardiogram (ECG) and PPG signals were recorded simultaneously for 120 s. PTT was calculated from the R wave of ECG and PPG waveform features. Eight PTT definitions were developed from different PPG waveform feature points. The raw PPG signals were preprocessed then further low-pass filtered. The difference between PTTs derived from preprocessed and filtered PPG signals, and the relative difference, were calculated and compared among five age groups and eight PTT definitions using the analysis of variance (ANOVA) or Scheirer-Ray-Hare test with post hoc analysis. Linear regression analysis was used to investigate the relationship between age and filtering-induced PTT changes. Results: Filtering-induced PTT difference and the relative difference were significantly influenced by age and PTT definition (p < 0.001 for both). Aging effect on filtering-induced PTT changes was consecutive with a monotonous trend under all PTT definitions. The age groups with maximum and minimum filtering-induced PTT changes depended on the definition. In all subjects, the PTT defined by maximum peak of PPG had the minimum filtering-induced PTT changes (mean: 16.16 ms and 5.65% for PTT difference and relative difference). The changes of PTT defined by maximum first PPG derivative had the strongest linear relationship with age (R-squared: 0.47 and 0.46 for PTT difference relative difference). Conclusion: The filtering-induced PTT changes are significantly influenced by age and PTT definition. These factors deserve further consideration to improve the accuracy of PPG-based cuffless blood pressure measurement using wearable sensors.

Real-Time Evaluation of Time-Domain Pulse Rate Variability Parameters in Different Postures and Breathing Patterns Using Wireless Photoplethysmography Sensor: Towards Remote Healthcare in Low-Resource Communities

Photoplethysmography (PPG) signals have been widely used in evaluating cardiovascular biomarkers, however, there is a lack of in-depth understanding of the remote usage of this technology and its viability for underdeveloped countries. This study aims to quantitatively evaluate the performance of a low-cost wireless PPG device in detecting ultra-short-term time-domain pulse rate variability (PRV) parameters in different postures and breathing patterns. A total of 30 healthy subjects were recruited. ECG and PPG signals were simultaneously recorded in 3 min using miniaturized wearable sensors. Four heart rate variability (HRV) and PRV parameters were extracted from ECG and PPG signals, respectively, and compared using analysis of variance (ANOVA) or Scheirer-Ray-Hare test with post hoc analysis. In addition, the data loss was calculated as the percentage of missing sampling points. Posture did not present statistical differences across the PRV parameters but a statistical difference between indicators was found. Strong variation was found for the RMSSD indicator in the standing posture. The sitting position in both breathing patterns demonstrated the lowest data loss (1.0 ± 0.6 and 1.0 ± 0.7) and the lowest percentage of different factors for all indicators. The usage of commercial PPG and BLE devices can allow the reliable extraction of the PPG signal and PRV indicators in real time.

Effect of intracranial pressure on photoplethysmographic waveform in different cerebral perfusion territories: A computational study

Background: Intracranial photoplethysmography (PPG) signals can be measured from extracranial sites using wearable sensors and may enable long-term non-invasive monitoring of intracranial pressure (ICP). However, it is still unknown if ICP changes can lead to waveform changes in intracranial PPG signals.

Aim: To investigate the effect of ICP changes on the waveform of intracranial PPG signals of different cerebral perfusion territories.

Methods: Based on lump-parameter Windkessel models, we developed a computational model consisting three interactive parts: cardiocerebral artery network, ICP model, and PPG model. We simulated ICP and PPG signals of three perfusion territories [anterior, middle, and posterior cerebral arteries (ACA, MCA, and PCA), all left side] in three ages (20, 40, and 60 years) and four intracranial capacitance conditions (normal, 20% decrease, 50% decrease, and 75% decrease). We calculated following PPG waveform features: maximum, minimum, mean, amplitude, min-to-max time, pulsatility index (PI), resistive index (RI), and max-to-mean ratio (MMR).

Results: The simulated mean ICPs in normal condition were in the normal range (8.87–11.35 mm Hg), with larger PPG fluctuations in older subject and ACA/PCA territories. When intracranial capacitance decreased, the mean ICP increased above normal threshold (&gt;20 mm Hg), with significant decreases in maximum, minimum, and mean; a minor decrease in amplitude; and no consistent change in min-to-max time, PI, RI, or MMR (maximal relative difference less than 2%) for PPG signals of all perfusion territories. There were significant effects of age and territory on all waveform features except age on mean.

Conclusion: ICP values could significantly change the value-relevant (maximum, minimum, and amplitude) waveform features of PPG signals measured from different cerebral perfusion territories, with negligible effect on shape-relevant features (min-to-max time, PI, RI, and MMR). Age and measurement site could also significantly influence intracranial PPG waveform.

Wavelet analysis of laser Doppler microcirculatory signals: Current applications and limitations

Laser Doppler flowmetry (LDF) has long been considered a gold standard for non-invasive assessment of skin microvascular function. Due to the laser Doppler (LD) microcirculatory signal's complex biological and physiological context, using spectral analysis is advisable to extract as many of the signal's properties as feasible. Spectral analysis can be performed using either a classical Fourier transform (FT) technique, which has the disadvantage of not being able to localize a signal in time, or wavelet analysis (WA), which provides both the time and frequency localization of the inspected signal. So far, WA of LD microcirculatory signals has revealed five characteristic frequency intervals, ranging from 0.005 to 2 Hz, each of which being related to a specific physiological influence modulating skin microcirculatory response, providing for a more thorough analysis of the signals measured in healthy and diseased individuals. Even though WA is a valuable tool for analyzing and evaluating LDF-measured microcirculatory signals, limitations remain, resulting in a lack of analytical standardization. As a more accurate assessment of human skin microcirculation may better enhance the prognosis of diseases marked by microvascular dysfunction, searching for improvements to the WA method is crucial from the clinical point of view. Accordingly, we have summarized and discussed WA application and its limitations when evaluating LD microcirculatory signals, and presented insight into possible future improvements. We adopted a novel strategy when presenting the findings of recent studies using WA by focusing on frequency intervals to contrast the findings of the various studies undertaken thus far and highlight their disparities.

Changes of oscillogram envelope maximum with blood pressure and aging: a quantitative observation

Objective.The oscillometric blood pressure (BP) measurement technique estimates BPs from analyzing the oscillometric cuff pressure waveform (oscillogram) envelope. The oscillogram envelope maximum is associated with physiological changes and influences BP measurement accuracy. We aim to quantitatively investigate the effect of BP and aging on the changes of oscillogram envelope maximum.Approach.Four hundred and sixty-two subjects (214 female, 248 male) were recruited. The cuff pressure was digitally recorded during linear cuff deflation to derive oscillogram envelopes and their maximums. Moderation analysis was performed to investigate whether the relationship between BP and envelope maximum was moderated by age. Subjects were divided into five age categories and three BP groups. The envelope maximums were compared between different BP and age categories to qualify their changes with increased BP and aging.Main results.Age has a significant moderating effect on the relationship between BP and envelope maximum (P < 0.05). The oscillogram envelope maximums increased significantly with increased BPs (P < 0.05 between each BP groups) and aging (P < 0.05 for > 60 years old groups in comparison with younger groups).Significance.This study experientially and theoretically concluded the BPs and aging are two important factors that influence the maximum value of the oscillogram envelope.

Affective Computing Based on Morphological Features of Photoplethysmography for Patients with Hypertension

Negative and positive emotions are the risk and protective factors for the cause and prognosis of hypertension. This study aimed to use five photoplethysmography (PPG) waveform indices and affective computing (AC) to discriminate the emotional states in patients with hypertension. Forty-three patients with essential hypertension were measured for blood pressure and PPG signals under baseline and four emotional conditions (neutral, anger, happiness, and sadness), and the PPG signals were transformed into the mean standard deviation of five PPG waveform indices. A support vector machine was used as a classifier. The performance of the classifier was verified by using resubstitution and six-fold cross-validation (CV) methods. Feature selectors, including full search and genetic algorithm (GA), were used to select effective feature combinations. Traditional statistical analyses only differentiated between the emotional states and baseline, whereas AC achieved 100% accuracy in distinguishing between the emotional states and baseline by using the resubstitution method. AC showed high accuracy rates when used with 10 waveform features in distinguishing the records into two, three, and four classes by applying a six-fold CV. The GA feature selector further boosted the accuracy to 78.97%, 74.22%, and 67.35% in two-, three-, and four-class differentiation, respectively. The proposed AC achieved high accuracy in categorizing PPG records into distinct emotional states with features extracted from only five waveform indices. The results demonstrated the effectiveness of the five indices and the proposed AC in patients with hypertension.

History of Brain Injury Alters Cerebral Haemodynamic Oscillations with Cardiac Influence

(1) Background: Cerebral autoregulation is altered during acute mild traumatic brain injury, or concussion. However, it is unknown how a history of concussion can impact cerebral haemodynamic activity during a task that elicits an autoregulatory response. (2) Methods: We assessed cerebral haemodynamic activity in those with a history of three or more concussions. The study included 44 retired athletes with concussion history and 25 control participants. We recorded participants' relative changes in right and left pre-frontal cortex oxygenation collected by near-infrared spectroscopy and continuous beat-to-beat blood pressure measured by finger photoplethysmography. Participants completed a 5-min seated rest followed by a 5-min repeated squat (10-s) stand (10-s) maneuver (0.05 Hz) to elicit a cerebral autoregulatory response. Wavelet transformation was applied to the collected signals, allowing separation into cardiac interval I (0.6 to 2 Hz), respiratory interval II (0.145 to 0.6 Hz), and smooth muscle cell interval III (0.052 to 0.145 Hz). (3) Results: Significant increases at cardiac interval I were found for the wavelet amplitude of oxy-haemoglobin and haemoglobin difference at the right pre-frontal cortex. No significant difference was found at the left pre-frontal cortex or the blood pressure wavelet amplitudes. (4) Conclusions: Contributions from cardiac activity to the pre-frontal cortex oxygenation are elevated when eliciting dynamic cerebral autoregulation in those with a history of three or more concussions.

Correlation Mapping of Perfusion Patterns in Cutaneous Tissue

Perfusion patterns of cutaneous tissue represent a valuable source of information about the state of the patient’s cardiovascular system and autonomic nervous system (ANS). This concept aims to observe the perfusion changes in the foot sole in two healthy individuals and two subjects affected by diabetes mellitus (DM). We use photoplethysmography imaging (PPGI) to monitor cutaneous perfusion changes. This method, in contrast to conventional contact photoplethysmography (PPG), allows the monitoring of skin perfusion with spatial distribution. We use a machine vision camera and an illumination system using the green light. To induce the perfusion changes, we perform an experiment in the form of a deep breathing test (DBT). The experiment consists of three stages, with the middle stage being the DBT. To evaluate spatial perfusion changes, we use a normalized measure of the correlation of PPGI signals with a reference PPG signal obtained from the foot’s little toe. This method also increases the signal-to-noise ratio (SNR). Subjects with DM shows different patterns of tissue perfusion changes compared to healthy subjects. The DM subjects show increased perfusion after DBT compared to the pre-DBT state, whereas in healthy subjects, the tissue perfusion does not reach the level of the pre-DBT phase. This work can be considered as proof of concept in developing a non-contact and non-intrusive monitoring system that allows a different view of microcirculatory damage in patients with diabetes mellitus, focusing on its spatial distribution.

A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device

Background: Uterine activity (UA) monitoring is an essential element of pregnancy management. The gold-standard intrauterine pressure catheter (IUPC) is invasive and requires ruptured membranes, while the standard-of-care, external tocodynamometry (TOCO)’s accuracy is hampered by obesity, maternal movements, and belt positioning. There is an urgent need to develop telehealth tools enabling patients to remotely access care. Here, we describe and demonstrate a novel algorithm enabling remote, non-invasive detection and monitoring of UA by analyzing the modulation of the maternal electrocardiographic and phonocardiographic signals. The algorithm was designed and implemented as part of a wireless, FDA-cleared device designed for remote pregnancy monitoring. Two separate prospective, comparative, open-label, multi-center studies were conducted to test this algorithm.

Methods: In the intrapartum study, 41 laboring women were simultaneously monitored with IUPC and the remote pregnancy monitoring device. Ten patients were also monitored with TOCO. In the antepartum study, 147 pregnant women were simultaneously monitored with TOCO and the remote pregnancy monitoring device.

Results: In the intrapartum study, the remote pregnancy monitoring device and TOCO had sensitivities of 89.8 and 38.5%, respectively, and false discovery rates (FDRs) of 8.6 and 1.9%, respectively. In the antepartum study, a direct comparison of the remote pregnancy monitoring device to TOCO yielded a sensitivity of 94% and FDR of 31.1%. This high FDR is likely related to the low sensitivity of TOCO.

Conclusion: UA monitoring via the new algorithm embedded in the remote pregnancy monitoring device is accurate and reliable and more precise than TOCO standard of care. Together with the previously reported remote fetal heart rate monitoring capabilities, this novel method for UA detection expands the remote pregnancy monitoring device’s capabilities to include surveillance, such as non-stress tests, greatly benefiting women and providers seeking telehealth solutions for pregnancy care.

The Quantitative Associations Between Near Infrared Spectroscopic Cerebrovascular Metrics and Cerebral Blood Flow: A Scoping Review of the Human and Animal Literature

Cerebral blood flow (CBF) is an important physiologic parameter that is vital for proper cerebral function and recovery. Current widely accepted methods of measuring CBF are cumbersome, invasive, or have poor spatial or temporal resolution. Near infrared spectroscopy (NIRS) based measures of cerebrovascular physiology may provide a means of non-invasively, topographically, and continuously measuring CBF. We performed a systematically conducted scoping review of the available literature examining the quantitative relationship between NIRS-based cerebrovascular metrics and CBF. We found that continuous-wave NIRS (CW-NIRS) was the most examined modality with dynamic contrast enhanced NIRS (DCE-NIRS) being the next most common. Fewer studies assessed diffuse correlation spectroscopy (DCS) and frequency resolved NIRS (FR-NIRS). We did not find studies examining the relationship between time-resolved NIRS (TR-NIRS) based metrics and CBF. Studies were most frequently conducted in humans and animal studies mostly utilized large animal models. The identified studies almost exclusively used a Pearson correlation analysis. Much of the literature supported a positive linear relationship between changes in CW-NIRS based metrics, particularly regional cerebral oxygen saturation (rSO2), and changes in CBF. Linear relationships were also identified between other NIRS based modalities and CBF, however, further validation is needed.

Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos

Shock is one of the major killers in intensive care units, and early interventions can potentially reverse it. In this study, we advance a noncontact thermal imaging modality for continuous monitoring of hemodynamic shock working on 1,03,936 frames from 406 videos recorded longitudinally upon 22 pediatric patients. Deep learning was used to preprocess and extract the Center-to-Peripheral Difference (CPD) in temperature values from the videos. This time-series data along with the heart rate was finally analyzed using Long-Short Term Memory models to predict the shock status up to the next 6 h. Our models achieved the best area under the receiver operating characteristic curve of 0.81 ± 0.06 and area under the precision-recall curve of 0.78 ± 0.05 at 5 h, providing sufficient time to stabilize the patient. Our approach, thus, provides a reliable shock prediction using an automated decision pipeline that can provide better care and save lives.

Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note

Wearable devices are burgeoning, and applications across numerous verticals are emerging, including human performance monitoring, at-home patient monitoring, and health tracking, to name a few. Off-the-shelf wearables have been developed with focus on portability, usability, and low-cost. As such, when deployed in highly ecological settings, wearable data can be corrupted by artifacts and by missing data, thus severely hampering performance. In this technical note, we overview a signal processing representation called the modulation spectrum. The representation quantifies the rate-of-change of different spectral magnitude components and is shown to separate signal from noise, thus allowing for improved quality measurement, quality enhancement, and noise-robust feature extraction, as well as for disease characterization. We provide an overview of numerous applications developed by the authors over the last decade spanning different wearable modalities and list the results obtained from experimental results alongside comparisons with various state-of-the-art benchmark methods. Open-source software is showcased with the hope that new applications can be developed. We conclude with a discussion on possible future research directions, such as context awareness, signal compression, and improved input representations for deep learning algorithms.

Metal Removal Kinetics, Bio-Accumulation and Plant Response to Nutrient Availability in Floating Treatment Wetland for Stormwater Treatment

Floating treatment wetland (FTW) is a recent innovation to remove nutrients from stormwater, but little is known about its effectiveness for metal removal. This study aims to test the hypothesis that the metal removal performance of FTWs will be affected by nutrient (NH3-N, NO3-N, and PO4-P) availability in stormwater. Two experiments were carried out in nutrient-deficient tap water, and two experiments were carried out in nutrient-rich lake water using four native Australian plants, namely Carex fascicularis, Juncus kraussii, Eleocharis acuta, and Baumea preissii. Up to 81% Cu and 44.9% Zn removal were achieved by the plants in 16 days in tap water. A reduction in Cu and Zn removal of 28.4–57.3% and 1.0–19.7%, respectively, was observed in lake water compared with tap water for the same duration. The kinetic analysis also confirmed that plant metal uptake rates slowed down in lake water (0.018–0.088 L/mg/day for Cu and 0.005–0.018 L/mg/day for Zn) compared to tap water (0.586–0.825 L/mg/day for Cu and 0.025–0.052 L/mg/day for Zn). A plant tissue analysis revealed that E. acuta and B. preissii bioaccumulated more than 1000 mg/kg of both metals in their tissue, indicating high metal accumulation capacities. To overcome the slower metal uptake rate problem due to nutrient availability, future studies can investigate multi-species plantations with nutrient stripping plants and metal hyper-accumulator plants.

Angiographic Pulse Wave Coherence in the Human Brain

A stroke volume of arterial blood that arrives to the brain housed in the rigid cranium must be matched over the cardiac cycle by an equivalent volume of ejected venous blood. We hypothesize that the brain maintains this equilibrium by organizing coherent arterial and venous pulse waves. To test this hypothesis, we applied wavelet computational methods to diagnostic cerebral angiograms in four human patients, permitting the capture and analysis of cardiac frequency phenomena from fluoroscopic images acquired at faster than cardiac rate. We found that the cardiac frequency reciprocal phase of a small region of interest (ROI) in a named artery predicts venous anatomy pixel-wise and that the predicted pixels reconstitute venous bolus passage timing. Likewise, a small ROI in a named vein predicts arterial anatomy and arterial bolus passage timing. The predicted arterial and venous pixel groups maintain phase complementarity across the bolus travel. We thus establish a novel computational method to analyze vascular pulse waves from minimally invasive cerebral angiograms and provide the first direct evidence of arteriovenous coupling in the intact human brain. This phenomenon of arteriovenous coupling may be a physiologic mechanism for how the brain precisely maintains mechanical equilibrium against volume displacement and kinetic energy transfer resulting from cyclical deformations with each heartbeat. The study also paves the way to study deranged arteriovenous coupling as an underappreciated pathophysiologic disturbance in a myriad of neurological pathologies linked by mechanical disequilibrium.

On the spatial phase distribution of cutaneous low-frequency perfusion oscillations

Distributed cutaneous tissue blood volume oscillations contain information on autonomic nervous system (ANS) regulation of cardiorespiratory activity as well as dominating thermoregulation. ANS associated with low-frequency oscillations can be quantified in terms of frequencies, amplitudes, and phase shifts. The relative order between these faculties may be disturbed by conditions colloquially termed ‘stress’. Photoplethysmography imaging, an optical non-invasive diagnostic technique provides information on cutaneous tissue perfusion in the temporal and spatial domains. Using the cold pressure test (CPT) in thirteen healthy volunteers as a well-studied experimental intervention, we present a method for evaluating phase shifts in low- and intermediate frequency bands in forehead cutaneous perfusion mapping. Phase shift changes were analysed in low- and intermediate frequency ranges from 0.05 Hz to 0.18 Hz. We observed that time waveforms increasingly desynchronised in various areas of the scanned area throughout measurements. An increase of IM band phase desynchronization observed throughout measurements was comparable in experimental and control group, suggesting a time effect possibly due to overshooting the optimal relaxation duration. CPT triggered an increase in the number of points phase-shifted to the reference that was specific to the low frequency range for phase-shift thresholds defined as π/4, 3π/8, and π/2 rad, respectively. Phase shifts in forehead blood oscillations may infer changes of vascular tone due to activity of various neural systems. We present an innovative method for the phase shift analysis of cutaneous tissue perfusion that appears promising to assess ANS change processes related to physical or psychological stress. More comprehensive studies are needed to further investigate the reliability and physiological significance of findings.

Choroidal Vascularity Index Changes After Exercise in Patients With Glaucoma

Purpose: To investigate the changes in choroidal vascular structures after exercise in patients with glaucoma using an image binarisation algorithm with enhanced-depth imaging optical coherence tomography.

Methods: Thirty-four eyes of 19 patients with primary open-angle glaucoma and 40 eyes of 20 normal subjects were included in the glaucoma and control groups, respectively. All subjects were evaluated before, immediately after, and 30 min after 20-min running at moderate speed. The subfoveal choroidal area was segmented into the luminal area (LA) and stromal area (SA), and the choroidal vascularity index (CVI) was measured by calculating the ratio of LA to the total choroidal area (TCA). The mean intraocular pressure (IOP), subfoveal choroidal thickness, CVI, SA, CA, and TCA were compared within and between both groups. The correlation between CVI, IOP, and other vascular indexes was investigated.

Results: In the glaucoma group, a significantly lower CVI was found immediately after exercise and recovered 30 min after exercise. Higher TCA and LA levels were demonstrated 30 min after exercise compared to immediately after exercise. In both groups, IOP decreased immediately after exercise but was restored after a 30-min rest. In the glaucoma group, there was a higher correlation between CVI and other choroidal vascular parameters than in the control group. There was no difference in IOP or choroidal parameters between the groups at different time points.

Conclusion: In patients with glaucoma, CVI decreased significantly immediately after exercise, indicating that the choroidal layer is affected by exercise and an unhealthy vascular regulatory mechanism.

Filtering-induced time shifts in photoplethysmography pulse features measured at different body sites: the importance of filter definition and standardization

Objective.The waveform of a photoplethysmography (PPG) signal depends on the measurement site and individual physiological conditions. Filtering can distort the morphology of the original PPG signal waveform and change the timing of pulse feature points on PPG signals. We aim to quantitatively investigate the effect of PPG signal morphology (related to measurement site) and type of pulse feature on the filtering-induced time shift (TS).Approach.60 s PPG signals were measured from six body sites (finger, wrist under (volar), wrist upper (dorsal), earlobe, and forehead) of 36 healthy adults. Using infinite impulse response digital filters which are common in PPG signal processing, PPG signals were prefiltered (band-pass, pass and stop bands: >0.5 Hz and <0.2 Hz for high-pass filter, <20 Hz and >30 Hz for low-pass filter) and then filtered (low-pass, pass and stop bands: <3 Hz and >5 Hz). Four pulse feature points were defined and extracted (peak, valley, maximal first derivative, and maximal second derivative). For each subject, overall TS and intra-subject TS variability in feature points were calculated as the mean and standard deviation of TS between prefiltered and filtered PPG signals in 50 cardiac cycles. Statistical testing was performed to investigate the effect of measurement site and type of pulse feature on overall TS and intra-subject TS variability.Main results.Measurement site, type of pulse feature, and their interaction had significant impacts on the overall TS and intra-subject TS variability (p < 0.001 for all). Valley and maximal second derivative showed higher overall TS than peak and maximal first derivative. Finger had higher overall TS and lower intra-subject TS variability than other measurement sites.Significance. Measurement site and type of pulse feature can significantly influence the timing of feature points on filtered PPG signals. Filtering parameters should be quoted to support the reproducibility of PPG-related studies.

Respiration Monitoring via Forcecardiography Sensors

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R² = 0.98) vs. 0.98, 0.11 s (R² = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.

Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients

Capabilities in continuous monitoring of key physiological parameters of disease have never been more important than in the context of the global COVID-19 pandemic. Soft, skin-mounted electronics that incorporate high-bandwidth, miniaturized motion sensors enable digital, wireless measurements of mechanoacoustic (MA) signatures of both core vital signs (heart rate, respiratory rate, and temperature) and underexplored biomarkers (coughing count) with high fidelity and immunity to ambient noises. This paper summarizes an effort that integrates such MA sensors with a cloud data infrastructure and a set of analytics approaches based on digital filtering and convolutional neural networks for monitoring of COVID-19 infections in sick and healthy individuals in the hospital and the home. Unique features are in quantitative measurements of coughing and other vocal events, as indicators of both disease and infectiousness. Systematic imaging studies demonstrate correlations between the time and intensity of coughing, speaking, and laughing and the total droplet production, as an approximate indicator of the probability for disease spread. The sensors, deployed on COVID-19 patients along with healthy controls in both inpatient and home settings, record coughing frequency and intensity continuously, along with a collection of other biometrics. The results indicate a decaying trend of coughing frequency and intensity through the course of disease recovery, but with wide variations across patient populations. The methodology creates opportunities to study patterns in biometrics across individuals and among different demographic groups.

Clinical Evaluation of Respiratory Rate Measurements on COPD (Male) Patients Using Wearable Inkjet-Printed Sensor

Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a progressive disease that causes long-term breathing problems. The reliable monitoring of respiratory rate (RR) is very important for the treatment and management of COPD. Based on inkjet printing technology, we have developed a stretchable and wearable sensor that can accurately measure RR on normal subjects. Currently, there is a lack of comprehensive evaluation of stretchable sensors in the monitoring of RR on COPD patients. We aimed to investigate the measurement accuracy of our sensor on COPD patients. Methodology: Thirty-five patients (Mean ± SD of age: 55.25 ± 13.76 years) in different stages of COPD were recruited. The measurement accuracy of our inkjet-printed (IJPT) sensor was evaluated at different body postures (i.e., standing, sitting at 90°, and lying at 45°) on COPD patients. The RR recorded by the IJPT sensor was compared with that recorded by the reference e-Health sensor using paired T-test and Wilcoxon signed-rank test. Analysis of variation (ANOVA) was performed to investigate if there was any significant effect of individual difference or posture on the measurement error. Statistical significance was defined as p-value less than 0.05. Results: There was no significant difference between the RR measurements collected by the IJPT sensor and the e-Health reference sensor overall and in three postures (p > 0.05 in paired T-tests and Wilcoxon signed-rank tests). The sitting posture had the least measurement error of −0.0542 ± 1.451 bpm. There was no significant effect of posture or individual difference on the measurement error or relative measurement error (p > 0.05 in ANOVA). Conclusion: The IJPT sensor can accurately measure the RR of COPD patients at different body postures, which provides the possibility for reliable monitoring of RR on COPD patients.