Nanocomposite Multimodal Sensor Array Integrated with Auxetic Structure for an Intelligent Biometrics System.

A multimodal sensor array, combining pressure and proximity sensing, has attracted considerable interest due to its importance in ubiquitous monitoring of cardiopulmonary health- and sleep-related biometrics. However, the sensitivity and dynamic range of prevalent sensors are often insufficient to detect subtle body signals. This study introduces a novel capacitive nanocomposite proximity-pressure sensor (NPPS) for detecting multiple human biometrics. NPPS consists of a carbon nanotube-paper composite (CPC) electrode and a percolating multiwalled carbon nanotube (MWCNT) foam enclosed in a MWCNT-coated auxetic frame. The fractured fibers in the CPC electrode intensify an electric field, enabling highly sensitive detection of proximity and pressure. When pressure is applied to the sensor, the synergic effect of MWCNT foam and auxetic deformation amplifies the sensitivity. The simple and mass-producible fabrication protocol allows for building an array of highly sensitive sensors to monitor human presence, sleep posture, and vital signs, including ballistocardiography (BCG). With the aid of a machine learning algorithm, the sensor array accurately detects blood pressure (BP) without intervention. This advancement holds promise for unrestricted vital sign monitoring during sleep or driving.

Hypotension During Vasopressor Infusion Occurs in Predictable Clusters: A Multicenter Analysis.

Background: Published evidence indicates that mean arterial pressure (MAP) below a goal range (hypotension) is associated with worse outcomes, though MAP management failures are common. We sought to characterize hypotension occurrences in ICUs and consider the implications for MAP management. Methods: Retrospective analysis of 3 hospitals' cohorts of adult ICU patients during continuous vasopressor infusion. Two cohorts were general, mixed ICU patients and one was exclusively acute spinal cord injury patients. "Hypotension-clusters" were defined where there were ≥10 min of cumulative hypotension over a 60-min period and "constant hypotension" was ≥10 continuous minutes. Trend analysis was performed (predicting future MAP using 14 min of preceding MAP data) to understand which hypotension-clusters could likely have been predicted by clinician awareness of MAP trends. Results: In cohorts of 155, 66, and 16 ICU stays, respectively, the majority of hypotension occurred within the hypotension-clusters. Failures to keep MAP above the hypotension threshold were notable in the bottom quartiles of each cohort, with hypotension durations of 436, 167, and 468 min, respectively, occurring within hypotension-clusters per day. Mean arterial pressure trend analysis identified most hypotension-clusters before any constant hypotension occurred (81.2%-93.6% sensitivity, range). The positive predictive value of hypotension predictions ranged from 51.4% to 72.9%. Conclusions: Across 3 cohorts, most hypotension occurred in temporal clusters of hypotension that were usually predictable from extrapolation of MAP trends.

BCG Signal Quality Assessment Based on Time-Series Imaging Methods.

This paper describes a signal quality classification method for arm ballistocardiogram (BCG), which has the potential for non-invasive and continuous blood pressure measurement. An advantage of the BCG signal for wearable devices is that it can easily be measured using accelerometers. However, the BCG signal is also susceptible to noise caused by motion artifacts. This distortion leads to errors in blood pressure estimation, thereby lowering the performance of blood pressure measurement based on BCG. In this study, to prevent such performance degradation, a binary classification model was created to distinguish between high-quality versus low-quality BCG signals. To estimate the most accurate model, four time-series imaging methods (recurrence plot, the Gramain angular summation field, the Gramain angular difference field, and the Markov transition field) were studied to convert the temporal BCG signal associated with each heartbeat into a 448 × 448 pixel image, and the image was classified using CNN models such as ResNet, SqueezeNet, DenseNet, and LeNet. A total of 9626 BCG beats were used for training, validation, and testing. The experimental results showed that the ResNet and SqueezeNet models with the Gramain angular difference field method achieved a binary classification accuracy of up to 87.5%.

Possibility of Pseudo-Obstruction in Lacrimal Canalicular Obstruction Diagnosed with Dacryocystography.

INTRODUCTION: Endoscopic dacryocystorhinostomy (DCR) is the treatment of choice for patients with lacrimal drainage system obstruction. Dacryocystography (DCG) is one of the most common preoperative studies and considered as a useful test demonstrating the anatomy of lacrimal drainage systems. OBJECTIVE: This study was designed to evaluate the diagnostic efficacy of DCG for canalicular obstruction and to compare surgical outcomes between true-obstruction versus pseudo-obstruction diagnosed with DCG. METHODS: A retrospective study was performed on 45 consecutive patients with lacrimal canalicular obstruction who had underwent endoscopic DCR with silicone tube insertion from January 2009 to December 2014 at a single tertiary hospital. A review of medical records included demographic data, preoperative symptoms and signs, results of intraoperative canalicular probing, and surgical outcomes including the postoperative symptom improvement and endoscopic finding. RESULTS: Of 45 patients, 34 patients (75.6%) had true-canalicular obstructions and 11 patients (24.4%) had pseudo-canalicular obstructions. The success rate of endoscopic DCR was 50% (17 of 34) in cases with true-canalicular obstruction while 90.9% (10 of 11) in pseudo-canalicular obstruction (p value <0.05). No intraoperative or postoperative complications including sinusitis or synechia were found. CONCLUSIONS: About a quarter of lacrimal canalicular obstruction cases diagnosed with DCG seem to be pseudo-obstruction. The success rate of endoscopic DCR in pseudo-canalicular obstruction is similar to that of saccal and nasolacrimal ductal obstruction.

Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals.

This paper presents a novel computational algorithm to estimate blood volume decompensation state based on machine learning (ML) analysis of multi-modal wearable-compatible physiological signals. To the best of our knowledge, our algorithm may be the first of its kind which can not only discriminate normovolemia from hypovolemia but also classify hypovolemia into absolute hypovolemia and relative hypovolemia. We realized our blood volume classification algorithm by (i) extracting a multitude of features from multi-modal physiological signals including the electrocardiogram (ECG), the seismocardiogram (SCG), the ballistocardiogram (BCG), and the photoplethysmogram (PPG), (ii) constructing two ML classifiers using the features, one to classify normovolemia vs. hypovolemia and the other to classify hypovolemia into absolute hypovolemia and relative hypovolemia, and (iii) sequentially integrating the two to enable multi-class classification (normovolemia, absolute hypovolemia, and relative hypovolemia). We developed the blood volume decompensation state classification algorithm using the experimental data collected from six animals undergoing normovolemia, relative hypovolemia, and absolute hypovolemia challenges. Leave-one-subject-out analysis showed that our classification algorithm achieved an F1 score and accuracy of (i) 0.93 and 0.89 in classifying normovolemia vs. hypovolemia, (ii) 0.88 and 0.89 in classifying hypovolemia into absolute hypovolemia and relative hypovolemia, and (iii) 0.77 and 0.81 in classifying the overall blood volume decompensation state. The analysis of the features embedded in the ML classifiers indicated that many features are physiologically plausible, and that multi-modal SCG-BCG fusion may play an important role in achieving good blood volume classification efficacy. Our work may complement existing computational algorithms to estimate blood volume compensatory reserve as a potential decision-support tool to provide guidance on context-sensitive hypovolemia therapeutic strategy.

Interpersonal motor synergy: coworking strategy depends on task constraints.

We investigated the role of task constraints on interpersonal interactions. Twenty-one pairs of coworkers performed a finger force production task on force sensors placed at two ends of a seesaw-like apparatus and matched a combined target force of 20 N for 23 s over 10 trials. There were two experimental conditions: 1) FIXED: the seesaw apparatus was mechanically held in place so that the only task constraint was to match the 20 N resultant force, and 2) MOVING: the lever in the apparatus was allowed to rotate freely around its fulcrum, acting like a seesaw, so an additional task constraint to (implicitly) balance the resultant moment was added. We hypothesized that the additional task constraint of moment stabilization imposed on the MOVING condition would deteriorate task performance compared with the FIXED condition; however, this was rejected, as the performance of the force matching task was similar between two conditions. We also hypothesized that the central nervous systems (CNSs) would employ distinct coworking strategies or interpersonal motor synergy (IPMS) between conditions to satisfy different task constraints, which was supported by our results. Negative covariance between coworker's forces in the FIXED condition suggested a force stabilization strategy, whereas positive covariance in the MOVING condition suggested a moment stabilization strategy, implying that independent CNSs adopt distinct IPMSs depending on task constraints. We speculate that in the absence of a central neural controller, shared visual and mechanical connections between coworkers may suffice to trigger modulations in the cerebellum of each CNS to satisfy competing task constraints.NEW & NOTEWORTHY To the best of our knowledge, this is the first study to investigate the coworking behavior or IPMS when an additional task constraint is imposed. Our proposed analytical framework quantifies IPMS and allows for investigating variability in offline (i.e., across multiple repetitions) and online (i.e., across time) control, which is novel in coworking research. Understanding variability while performing a task is essential, as repeating a task is not always possible, as in therapeutic contexts.

Pulse arrival time, a novel sleep cardiovascular marker: the multi-ethnic study of atherosclerosis.

BACKGROUND: Pulse arrival time (PAT) is commonly used to estimate blood pressure response. We hypothesised that PAT response to obstructive respiratory events would be associated with increased cardiovascular risk in people with obstructive sleep apnoea. METHODS: PAT, defined as the time interval between electrocardiography R wave and pulse arrival by photoplethysmography, was measured in the Multi-Ethnic Study of Atherosclerosis Sleep study participants. The PAT response to apnoeas/hypopnoeas was defined as the area under the PAT waveform following respiratory events. Cardiovascular outcomes included markers of subclinical cardiovascular disease (CVD): left ventricular mass, carotid plaque burden score and coronary artery calcification (CAC) (cross-sectional) and incident composite CVD events (prospective). Multivariable logistic and Cox proportional hazard regressions were performed. RESULTS: A total of 1407 participants (mean age 68.4 years, female 47.5%) were included. Higher PAT response (per 1 SD increase) was associated with higher left ventricular mass (5.7 g/m2 higher in fourth vs first quartile, p<0.007), higher carotid plaque burden score (0.37 higher in fourth vs first quartile, p=0.02) and trended to greater odds of CAC (1.44, 95% CI 0.98 to 2.15, p=0.06). A total of 65 incident CVD events were observed over the mean of 4.1 (2.6) years follow-up period. Higher PAT response was associated with increased future CVD events (HR: 1.20, 95% CI 1.02 to 1.42, p=0.03). CONCLUSION: PAT is independently associated with markers of subclinical CVD and incident CVD events. Respiratory-related PAT response is a novel and promising polysomnography metric with cardiovascular implications.

Children with epilepsy demonstrate macro- and microstructural changes in the thalamus, putamen, and amygdala.

PURPOSE: Despite evidence for macrostructural alteration in epilepsy patients later in life, little is known about the underlying pathological or compensatory mechanisms at younger ages causing these alterations. The aim of this work was to investigate the impact of pediatric epilepsy on the central nervous system, including gray matter volume, cerebral blood flow, and water diffusion, compared with neurologically normal children. METHODS: Inter-ictal magnetic resonance imaging data was obtained from 30 children with epilepsy ages 1-16 (73% F, 27% M). An atlas-based approach was used to determine values for volume, cerebral blood flow, and apparent diffusion coefficient in the cerebral cortex, hippocampus, thalamus, caudate, putamen, globus pallidus, amygdala, and nucleus accumbens. These values were then compared with previously published values from 100 neurologically normal children using a MANCOVA analysis. RESULTS: Most brain volumes of children with epilepsy followed a pattern similar to typically developing children, except for significantly larger putamen and amygdala. Cerebral blood flow was also comparable between the groups, except for the putamen, which demonstrated decreased blood flow in children with epilepsy. Diffusion (apparent diffusion coefficient) showed a trend towards higher values in children with epilepsy, with significantly elevated diffusion within the thalamus in children with epilepsy compared with neurologically normal children. CONCLUSION: Children with epilepsy show statistically significant differences in volume, diffusion, and cerebral blood flow within their thalamus, putamen, and amygdala, suggesting that epilepsy is associated with structural changes of the central nervous system influencing brain development and potentially leading to poorer neurocognitive outcomes.

Observer-Based Deconvolution of Deterministic Input in Coprime Multichannel Systems With Its Application to Noninvasive Central Blood Pressure Monitoring.

Estimating central aortic blood pressure (BP) is important for cardiovascular (CV) health and risk prediction purposes. CV system is a multichannel dynamical system that yields multiple BPs at various body sites in response to central aortic BP. This paper concerns the development and analysis of an observer-based approach to deconvolution of unknown input in a class of coprime multichannel systems applicable to noninvasive estimation of central aortic BP. A multichannel system yields multiple outputs in response to a common input. Hence, the relationship between any pair of two outputs constitutes a hypothetical input-output system with unknown input embedded as a state. The central idea underlying our approach is to derive the unknown input by designing an observer for the hypothetical input-output system. In this paper, we developed an unknown input observer (UIO) for input deconvolution in coprime multichannel systems. We provided a universal design algorithm as well as meaningful physical insights and inherent performance limitations associated with the algorithm. The validity and potential of our approach were illustrated using a case study of estimating central aortic BP waveform from two noninvasively acquired peripheral arterial pulse waveforms. The UIO could reduce the root-mean-squared error (RMSE) associated with the central aortic BP by up to 27.5% and 28.8% against conventional inverse filtering (IF) and peripheral arterial pulse scaling techniques.

Clinicopathological and Radiological Features of Chronic Rhinosinusitis with Eosinophilic Mucin in Chungcheong Province of Korea.

BACKGROUND: Chronic rhinosinusitis (CRS) with eosinophilic mucin is considered rare in Korea. The object of this study was to categorize CRS patients with eosinophilic mucin into several groups and compared the groups based on their clinicopathological and radiological features. METHODS: In total, 105 CRS patients with eosinophilic mucin from four tertiary medical centers which are located at Chungcheong province of Korea were included for this study. The patients were divided into four groups for analysis, based on the presence or absence of an allergy (A) to a fungus or fungal element (F) in the mucin. The following were the four groups: allergic fungal rhinosinusitis (AFRS, A+F+), AFRS-like sinusitis (A+F-), eosinophilic fungal rhinosinusitis (EFRS, A-F+), and eosinophilic mucin rhinosinusitis (EMRS, A-F-). Their clinical manifestation, the presence of associated disease, radiological finding, treatment, and treatment outcome were reviewed and compared. RESULTS: There were no patients in the AFRS-like sinusitis group, 47 patients were assigned to the AFRS group, 27 to the EFRS group, and 41 to the EMRS group. Patients of AFRS group showed a significantly higher association with allergic rhinitis than did the other groups. The mean total serum IgE level in the AFRS patients was significantly higher than in the EFRS and EMRS patients. In the AFRS group and EFRS group, 67.6% and 74.1% had unilateral disease, respectively, in contrast to the EMRS group (4.9%). The mean Hounsfield unit values of the area of high attenuation in the AFRS patients were significantly higher than those in the other groups. CONCLUSIONS: Significant clinicopathological differences existed among the subgroups of CRS with eosinophilic mucin. AFRS tends to be an allergic response to colonizing fungi in atopic individuals. In EFRS, local allergies to fungi might play a role in the disease. EMRS is thought to be unconnected with fungal allergies, and it showed different form compared with the AFRS and EFRS groups.

Minimally Invasive Technique to Reduce the Isolated Anterior Wall Fracture of the Frontal Sinus.

Conventional open reduction and internal fixation of frontal sinus anterior wall fractures are associated with risks of visible scarring and limited access to the nasofrontal duct. The goal of this study was to report the minimally invasive surgical techniques and their results in cases with frontal sinus anterior wall fractures. A retrospective study was performed on 20 consecutive cases of isolated anterior wall fractures of the frontal sinus between July, 2008 and February, 2017. Causes of injury, interval between the injury and operation, and operation time were reviewed. The fractures were reduced using the minimally invasive techniques of endoscopic endonasal reduction or reduction through a small trephination. Anatomical and aesthetic outcomes were evaluated, and postoperative complications were reviewed. The fractures were reduced with endoscopic endonasal techniques in 11 patients and through a small trephination with a minimal incision in the forehead in 9 patients. The fractures were successfully reduced in all cases. The mean follow-up period was 21.2 months, and no postoperative complications were observed. For isolated anterior wall fractures of the frontal sinus, minimally invasive techniques, such as endonasal endoscopic reduction or reduction through a small trephination, are safe and effective options.

Unobtrusive Estimation of Cardiovascular Parameters with Limb Ballistocardiography.

This study investigates the potential of the limb ballistocardiogram (BCG) for unobtrusive estimation of cardiovascular (CV) parameters. In conjunction with the reference CV parameters (including diastolic, pulse, and systolic pressures, stroke volume, cardiac output, and total peripheral resistance), an upper-limb BCG based on an accelerometer embedded in a wearable armband and a lower-limb BCG based on a strain gauge embedded in a weighing scale were instrumented simultaneously with a finger photoplethysmogram (PPG). To standardize the analysis, the more convenient yet unconventional armband BCG was transformed into the more conventional weighing scale BCG (called the synthetic weighing scale BCG) using a signal processing procedure. The characteristic features were extracted from these BCG and PPG waveforms in the form of wave-to-wave time intervals, wave amplitudes, and wave-to-wave amplitudes. Then, the relationship between the characteristic features associated with (i) the weighing scale BCG-PPG pair and (ii) the synthetic weighing scale BCG-PPG pair versus the CV parameters, was analyzed using the multivariate linear regression analysis. The results indicated that each of the CV parameters of interest may be accurately estimated by a combination of as few as two characteristic features in the upper-limb or lower-limb BCG, and also that the characteristic features recruited for the CV parameters were to a large extent relevant according to the physiological mechanism underlying the BCG.

In-depth investigations of adolescents and adults with holoprosencephaly identify unique characteristics.

PurposeWith improved medical care, some individuals with holoprosencephaly (HPE) are surviving into adulthood. We investigated the clinical manifestations of adolescents and adults with HPE and explored the underlying molecular causes.MethodsParticipants included 20 subjects 15 years of age and older. Clinical assessments included dysmorphology exams, cognitive testing, swallowing studies, ophthalmic examination, and brain magnetic resonance imaging. Genetic testing included chromosomal microarray, Sanger sequencing for SHH, ZIC2, SIX3, and TGIF, and whole-exome sequencing (WES) of 10 trios.ResultsSemilobar HPE was the most common subtype of HPE, seen in 50% of the participants. Neurodevelopmental disabilities were found to correlate with HPE subtype. Factors associated with long-term survival included HPE subtype not alobar, female gender, and nontypical facial features. Four participants had de novo pathogenic variants in ZIC2. WES analysis of 11 participants did not reveal plausible candidate genes, suggesting complex inheritance in these cases. Indeed, in two probands there was a history of uncontrolled maternal type 1 diabetes.ConclusionIndividuals with various HPE subtypes can survive into adulthood and the neurodevelopmental outcomes are variable. Based on the facial characteristics and molecular evaluations, we suggest that classic genetic causes of HPE may play a smaller role in this cohort.

Control-oriented physiological modeling of hemodynamic responses to blood volume perturbation.

This paper presents a physiological model to reproduce hemodynamic responses to blood volume perturbation. The model consists of three sub-models: a control-theoretic model relating blood volume response to blood volume perturbation; a simple physics-based model relating blood volume to stroke volume and cardiac output; and a phenomenological model relating cardiac output to blood pressure. A unique characteristic of this model is its balance for simplicity and physiological transparency. Initial validity of the model was examined using experimental data collected from 11 animals. The model may serve as a viable basis for the design and evaluation of closed-loop fluid resuscitation controllers.

Prognostic factors of locally invasive well-differentiated thyroid carcinoma involving the trachea.

To report our experience with tracheal invasive thyroid carcinoma with emphasis on clinical characteristics and treatment modalities, and to identify the prognostic factors for tracheal invasive thyroid carcinoma. Totally 1919 patients underwent surgical extirpation of thyroid cancer from 1990 to 2010. Among them, 65 patients had well-differentiated thyroid cancer with tracheal invasion. The incidence was higher in male and older patients. Patients were treated with tracheal shave excision (n = 18), tracheal resection (n = 37) and total laryngectomy (n = 10). Locoregional recurrence occurred in 39 patients, and metastasis occurred in 25 patients. Simultaneous involvement of the trachea and the esophagus was associated with locoregional recurrence (p = 0.039) in univariate analysis, but not confirmed by multivariate analysis. There was significant difference in the disease-specific survival (DSS) according to laryngeal involvement (p = 0.002). All the patient in the shave excision group survived until the end of the study period. Although it is categorized in same classification of T4a, simultaneous involvement of the trachea and the esophagus showed higher locoregional recurrence and laryngeal involvement showed lower DSS. Despite the invasion of thyroid cancer into the adjacent aerodigestive tract, many patients showed long survival when they underwent appropriate surgery.

The role of tactile sensation in online and offline hierarchical control of multi-finger force synergy.

The hand, one of the most versatile but mechanically redundant parts of the human body, must overcome imperfect motor commands and inherent noise in both the sensory and motor systems in order to produce desired motor actions. For example, it is nearly impossible to produce a perfectly consistent note during a single violin stroke or to produce the exact same note over multiple strokes, which we denote online and offline control, respectively. To overcome these challenges, the central nervous system synergistically integrates multiple sensory modalities and coordinates multiple motor effectors. Among these sensory modalities, tactile sensation plays an important role in manual motor tasks by providing hand-object contact information. The purpose of this study was to investigate the role of tactile feedback in individual finger actions and multi-finger interactions during constant force production tasks. We developed analytical techniques for the linear decomposition of the overall variance in the motor system in both online and offline control. We removed tactile feedback from the fingers and demonstrated that tactile sensors played a critical role in the online control of synergistic interactions between fingers. In contrast, the same sensors did not contribute to offline control. We also demonstrated that when tactile feedback was removed from the fingers, the combined motor output of individual fingers did not change while individual finger behaviors did. This finding supports the idea of hierarchical control where individual fingers at the lower level work together to stabilize the performance of combined motor output at the higher level.

Data-driven lossy tube-load modeling of arterial tree: in-human study.

In this paper, we present and validate a data-driven method to lossy tube-load modeling of arterial tree in humans. In the proposed method, the lossy tube-load model is fitted to central aortic and peripheral blood pressure (BP) waves in the time domain. For this purpose, we employ a time-domain lossy tube-load model in which the wave propagation constant is formulated to two terms: one responsible for the alteration of wave amplitude and the other for the transport delay. Using the experimental BP data collected from 17 cardiac surgery patients, we showed that the time-domain lossy tube-load model is able to accurately represent the relation between central aortic versus upper-limb and lower-limb BP waves. In addition, the comparison of lossy versus lossless tube-load models revealed that (1) the former outperformed the latter in general with the root-mean-squared errors (RMSE) of 3.1 mm Hg versus 3.5 mm Hg, respectively (p-value < 0.05), and (2) the efficacy of the former over the latter was more clearly observed in case the normalized difference in the mean central aortic versus peripheral BP was large; when the difference was >5% of the underlying mean BP, lossy and lossless models showed the RMSE of 2.7 mm Hg and 3.7 mm Hg, respectively (p-value < 0.05).

A Physical Model-Based Approach to One-Point Calibration of Pulse Transit Time to Blood Pressure.

OBJECTIVE: To develop a novel physical model-based approach to enable 1-point calibration of pulse transit time (PTT) to blood pressure (BP). METHODS: The proposed PTT-BP calibration model is derived by combining the Bramwell-Hill equation and a phenomenological model of the arterial compliance (AC) curve. By imposing a physiologically plausible constraint on the skewness of AC at positive and negative transmural pressures, the number of tunable parameters in the PTT-BP calibration model reduces to 1. Hence, as opposed to most existing PTT-BP calibration models requiring multiple (≥2) PTT-BP measurements to personalize, the PTT-BP calibration model can be personalized to an individual subject using a single PTT-BP measurement pair. Equipped with the physically relevant PTT-AC and AC-BP relationships, the proposed approach may serve as a universal means to calibrate PTT to BP over a wide BP range. The validity and proof-of-concept of the proposed approach were evaluated using PTT and BP measurements collected from 22 healthy young volunteers undergoing large BP changes. RESULTS: The proposed approach modestly yet significantly outperformed an empiric linear PTT-BP calibration with a group-average slope and subject-specific intercept in terms of bias (5.5 mmHg vs 6.4 mmHg), precision (8.4 mmHg vs 9.4 mmHg), mean absolute error (7.8 mmHg vs 8.8 mmHg), and root-mean-squared error (8.7 mmHg vs 10.3 mmHg, all in the case of diastolic BP). CONCLUSION: We demonstrated the preliminary proof-of-concept of an innovative physical model-based approach to one-point PTT-BP calibration. SIGNIFICANCE: The proposed physical model-based approach has the potential to enable more accurate and convenient calibration of PTT to BP.

Detection of Internal Hemorrhage via Sequential Inference: An In Silico Feasibility Study.

This paper investigates the feasibility of detecting and estimating the rate of internal hemorrhage based on continuous noninvasive hematocrit measurement. A unique challenge in hematocrit-based hemorrhage detection is that hematocrit decreases in response to hemorrhage and resuscitation with fluids, which makes hemorrhage detection during resuscitation challenging. We developed two sequential inference algorithms for detection of internal hemorrhage based on the Luenberger observer and the extended Kalman filter. The sequential inference algorithms use fluid resuscitation dose and hematocrit measurement as inputs to generate signatures to enable detection of internal hemorrhage. In the case of the extended Kalman filter, the signature is nothing but inferred hemorrhage rate, which allows it to also estimate internal hemorrhage rate. We evaluated the proof-of-concept of these algorithms based on in silico evaluation in 100 virtual patients subject to diverse hemorrhage and resuscitation rates. The results showed that the sequential inference algorithms outperformed naïve internal hemorrhage detection based on the decrease in hematocrit when hematocrit noise level was 1% (average F1 score: Luenberger observer 0.80; extended Kalman filter 0.76; hematocrit 0.59). Relative to the Luenberger observer, the extended Kalman filter demonstrated comparable internal hemorrhage detection performance and superior accuracy in estimating the hemorrhage rate. The analysis of the dependence of the sequential inference algorithms on measurement noise and plant parametric uncertainty showed that small (≤1%) hematocrit noise level and personalization of sequential inference algorithms may enable continuous noninvasive detection of internal hemorrhage and estimation of its rate.

A GENERATIVE APPROACH TO TESTING THE PERFORMANCE OF PHYSIOLOGICAL CONTROL ALGORITHMS.

Background: Physiological closed-loop control algorithms play an important role in the development of autonomous medical care systems, a promising area of research that has the potential to deliver healthcare therapies meeting each patient's specific needs. Computational approaches can support the evaluation of physiological closed-loop control algorithms considering various sources of patient variability that they may be presented with. Method of Approach: In this paper, we present a generative approach to testing the performance of physiological closed-loop control algorithms. This approach exploits a generative physiological model (which consists of stochastic and dynamic components that represent diverse physiological behaviors across a patient population) to generate a select group of virtual subjects. By testing a physiological closed-loop control algorithm against this select group, the approach estimates the distribution of relevant performance metrics in the represented population. We illustrate the promise of this approach by applying it to a practical case study on testing a closed-loop fluid resuscitation control algorithm designed for hemodynamic management. Results: In this context, we show that the proposed approach can test the algorithm against virtual subjects equipped with a wide range of plausible physiological characteristics and behavior, and that the test results can be used to estimate the distribution of relevant performance metrics in the represented population. Conclusions: In sum, the generative testing approach may offer a practical, efficient solution for conducting pre-clinical tests on physiological closed-loop control algorithms.