Papers by Francesco Vicario
Frontiers in Cardiovascular Medicine
Cardiogenic shock (CS) is a severe condition with in-hospital mortality of up to 50%. Patients wh... more Cardiogenic shock (CS) is a severe condition with in-hospital mortality of up to 50%. Patients who develop CS may have previous cardiac history, but that may not always be the case, adding to the challenges in optimally identifying and managing these patients. Patients may present to a medical facility with CS or develop CS while in the emergency department (ED), in a general inpatient ward (WARD) or in the critical care unit (CC). While different clinical pathways for management exist once CS is recognized, there are challenges in identifying the patients in a timely manner, in all settings, in a timeframe that will allow proper management. We therefore developed and evaluated retrospectively a machine learning model based on the XGBoost (XGB) algorithm which runs automatically on patient data from the electronic health record (EHR). The algorithm was trained on 8 years of de-identified data (from 2010 to 2017) collected from a large regional healthcare system. The input variables ...
Modeling, Simulation and Optimization of Complex Processes HPSC 2015, 2017
Real-time noninvasive estimation of respiratory mechanics in spontaneously breathing patients is ... more Real-time noninvasive estimation of respiratory mechanics in spontaneously breathing patients is still an open problem in the field of critical care. Even assuming that the system is a simplistic first-order single-compartment model, the presence of unmeasured patient effort still makes the problem complex since both the parameters and part of the input are unknown. This paper presents an approach to overcome the underdetermined nature of the mathematical problem by infusing physiological knowledge into the estimation process and using it to construct an optimization problem subject to physiological constraints. As it relies only on measurements available on standard ventilators, namely the flow and pressure at the patient's airway opening, the approach is noninvasive. Additionally, breath by breath, it continually provides estimates of the patient respiratory resistance and elastance as well as of the muscle effort waveform without requiring maneuvers that would interfere with the desired ventilation pattern.
Inflation of hollow elastic structures can become unstable and exhibit a runaway phenomenon if th... more Inflation of hollow elastic structures can become unstable and exhibit a runaway phenomenon if the tension in their walls does not rise rapidly enough with increasing volume. Biological systems avoid such inflation instability for reasons that remain poorly understood. This is best exemplified by the lung, which inflates over its functional volume range without instability. The goal of this study was to determine how the constituents of lung parenchyma determine tissue stresses that protect alveoli from instability-related overdistension during inflation. We present an analytical model of a thick-walled alveolus composed of wavy elastic fibres, and investigate its pressure–volume behaviour under large deformations. Using second-harmonic generation imaging, we found that collagen waviness follows a β distribution. Using this distribution to fit human pressure–volume curves, we estimated collagen and elastin effective stiffnesses to be 1247 kPa and 18.3 kPa, respectively. Furthermore,...
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017
In this paper we present a method for the estimation of leaks in non-invasive ventilation. Accura... more In this paper we present a method for the estimation of leaks in non-invasive ventilation. Accurate estimation of leaks is a key component of a ventilator, since it determines the ventilator performance in terms of patientventilator synchrony and air volume delivery. In particular, in non-invasive ventilation, the patient flow is significantly different from the flow measured at the ventilator outlet. This is mostly due to the vent orifice along the tube that is used for exhalation, but also to the non-intentional leaks that occur elsewhere in the circuit (e.g., at the mask). Such leaks are traditionally quantified via a model with two parameters, but only one of them is continually updated-the other is fixed. The new algorithm allows for breath-by-breath update of both parameters. This was made possible by leveraging a model describing the patient respiratory mechanics.
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017
Typical modern mechanical ventilators offer the clinician the possibility of automatically perfor... more Typical modern mechanical ventilators offer the clinician the possibility of automatically performing end-inspiratory occlusion maneuvers. The static conditions induced by such maneuvers are indeed favorable to estimating patient's respiratory mechanics in terms of total resistance (R) and elastance (E). These are parameters of wide clinical interest. However, in the presence of intrinsic PEEP, the standard formula used to compute E via the occlusion maneuver is known to be inaccurate. In this paper we propose an alternative method for the estimation of E via the occlusion maneuver that eliminates the bias by leveraging concepts derived from physiological modeling of the respiratory system dynamics. The proposed method is also capable of accounting for respiratory efforts triggering the breath, and hence can be applied in both passive and spontaneously breathing conditions.
Observer/Kalman filter IDentification (OKID) is a successful approach for the estimation, from me... more Observer/Kalman filter IDentification (OKID) is a successful approach for the estimation, from measured input-output data, of the linear state-space model describing the dynamic behavior of a structure. From such a mathematical model, it is possible to recover the modal parameters, which can be exploited to update a detailed numerical model of the structure, e.g. a Finite Element Model (FEM), to be used to predict the structural response to future excitation and to evaluate damage scenarios. This paper extends OKID to output-only system identification, i.e. to the case where only the response of the structure is measured and the input is unknown. The approach is suitable for structural health monitoring based on modal parameters, in particular for those civil infrastructures whose excitation is random in nature and in the way it is applied to the structure (e.g. wind, traffic) and therefore is difficult to measure. The paper rigorously proves the applicability of the OKID approach t...
This paper presents a unified approach for the identification of linear state-space models from i... more This paper presents a unified approach for the identification of linear state-space models from input-output measurements in the presence of noise. It is based on the established Observer/Kalman filter IDentification (OKID) method of which it proposes a new formulation capable of transforming a stochastic identification problem into a (simpler) deterministic problem, where the Kalman filter corresponding to the unknown system and the unknown noise covariances is identified. The system matrices are then recovered from the identified Kalman filter. The Kalman filter can be identified with any deterministic identification method for linear state-space models, giving rise to numerous new algorithms and establishing the Kalman filter as the unifying bridge from stochastic to deterministic problems in system identification.
This paper formulates a bilinear observer for a bilinear state-space model. Relationship between ... more This paper formulates a bilinear observer for a bilinear state-space model. Relationship between the bilinear observer gains and the interaction matrices are established and used in the design of such observer gains from input-output data. In the absence of noise, the question of whether a deadbeat bilinear observer exists that would cause the state estimation error to converge to zero identically in a finite number of time steps is addressed. In the presence of noise, an optimal bilinear observer that minimizes the state estimation error in the same manner that a Kalman filter does for a linear system is presented. Numerical results illustrate both the theoretical and computational aspects of the proposed algorithms.
Modeling, Simulation and Optimization of Complex Processes HPSC 2015, 2017
This paper is a brief introduction to the interaction matrices. Originally formulated as a parame... more This paper is a brief introduction to the interaction matrices. Originally formulated as a parameter compression mechanism, the interaction matrices offer a unifying framework to treat a wide range of problems in system identification and control. We retrace the origin of the interaction matrices, and describe their applications in selected problems in system identification.
Bilinear systems offer a promising approach for nonlinear control because a broad class of nonlin... more Bilinear systems offer a promising approach for nonlinear control because a broad class of nonlinear problems can be reformulated and approximated in bilinear form. System identification is a technique to obtain such a bilinear approximation for a nonlinear system from input-output data. Recent discrete-time bilinear model identification methods rely on Input-Output-to-State Representations (IOSRs) derived via the interaction matrix technique. A new formulation of these methods is given by establishing a correspondence between interaction matrices and the gains of full-order bilinear state observers. The new interpretation of the identification methods highlights the possibility of utilizing minimal-order bilinear state observers to derive new IOSRs. The existence of such observers is discussed and shown to be guaranteed for special classes of bilinear systems. New bilinear system identification algorithms are developed and the corresponding computational advantages are illustrated ...
Bilinear systems offer a promising approach for nonlinear control because a broad class of nonlin... more Bilinear systems offer a promising approach for nonlinear control because a broad class of nonlinear problems can be reformulated in bilinear form. In this paper system identification is shown to be a technique to obtain such a bilinear approximation of a nonlinear system. Recent discrete-time bilinear model identification methods rely on Input-Output-to-State Representations. These IOSRs are exact only for a certain class of bilinear systems, and they are also limited by high dimensionality and explicit bounds on the input magnitude. This paper offers new IOSRs where the bilinear system is treated as a linear time-varying system through the use of specialized input signals. All the mentioned limitations are overcome by the new approach, leading to more accurate and less computationally demanding identification methods for bilinear discrete-time models, which are also shown via examples to be applicable to the identification of bilinear models approximating more general nonlinear sy...
Bilinear systems are important per se since several phenomena in engineering and other fields are... more Bilinear systems are important per se since several phenomena in engineering and other fields are inherently bilinear. Even more interestingly, bilinear systems can approximate more general nonlinear systems, providing a promising approach to handle various nonlinear identification and control problems, such as satellite attitude control. This paper develops and demonstrates via numerical examples a method for discrete-time state-space model identification for bilinear systems in the presence of noise in the process and in the measurements. The formulation relies on a bilinear observer which is proven to have properties similar to the linear Kalman filter under the sole additional assumption of stationary white excitation input, and on a novel approach to system identification based on the estimation of the observer residuals. The latter are used to construct a new, noise-free identification problem, in which the observer is identified and the matrices of the system state-space model are recovered. The resulting method represents the bilinear counterpart of the Observer/Kalman filter Identification (OKID) approach for linear systems, originally developed for the identification of lightly-damped structures and distributed by NASA.
When excited by an input consisting of a number of discrete levels, a bilinear system becomes a l... more When excited by an input consisting of a number of discrete levels, a bilinear system becomes a linear time-varying system whose dynamics switches from one linear subsystem to another depending on the input level. This paper describes an identification method that uses the concept of a superstate of a linear switching system as a superstate of the bilinear system. In a superspace method, these superstates are used directly to identify a bilinear system model. In a subspace method, two or more superstate representations are intersected to find a reduced dimension subspace prior to identification of a bilinear model.
Critical Care, 2021
Background Timely recognition of hemodynamic instability in critically ill patients enables incre... more Background Timely recognition of hemodynamic instability in critically ill patients enables increased vigilance and early treatment opportunities. We develop the Hemodynamic Stability Index (HSI), which highlights situational awareness of possible hemodynamic instability occurring at the bedside and to prompt assessment for potential hemodynamic interventions. Methods We used an ensemble of decision trees to obtain a real-time risk score that predicts the initiation of hemodynamic interventions an hour into the future. We developed the model using the eICU Research Institute (eRI) database, based on adult ICU admissions from 2012 to 2016. A total of 208,375 ICU stays met the inclusion criteria, with 32,896 patients (prevalence = 18%) experiencing at least one instability event where they received one of the interventions during their stay. Predictors included vital signs, laboratory measurements, and ventilation settings. Results HSI showed significantly better performance compared ...
Journal of The Royal Society Interface, 2021
Inflation of hollow elastic structures can become unstable and exhibit a runaway phenomenon if th... more Inflation of hollow elastic structures can become unstable and exhibit a runaway phenomenon if the tension in their walls does not rise rapidly enough with increasing volume. Biological systems avoid such inflation instability for reasons that remain poorly understood. This is best exemplified by the lung, which inflates over its functional volume range without instability. The goal of this study was to determine how the constituents of lung parenchyma determine tissue stresses that protect alveoli from instability-related overdistension during inflation. We present an analytical model of a thick-walled alveolus composed of wavy elastic fibres, and investigate its pressure–volume behaviour under large deformations. Using second-harmonic generation imaging, we found that collagen waviness follows a beta distribution. Using this distribution to fit human pressure–volume curves, we estimated collagen and elastin effective stiffnesses to be 1247 kPa and 18.3 kPa, respectively. Furthermo...
The COVID-19 pandemic is overwhelming healthcare systems worldwide. A significant portion of COVI... more The COVID-19 pandemic is overwhelming healthcare systems worldwide. A significant portion of COVID-19 patients develop pneumonia and acute respiratory distress syndrome (ARDS), necessitating ventilator support. Some health systems do not have the capacity to accommodate this surge in ventilator demand, leading to shortages and inevitable mortality. Some clinicians have, of necessity, jerry-rigged ventilators to support multiple patients, but these devices lack protected air streams or individualized controls for each patient. Moreover, some have not been tested under conditions of ARDS. We have developed the Individualized System for Augmenting Ventilator Efficacy (iSAVE), a rapidly deployable platform to more safely use a single ventilator to simultaneously support multiple critically-ill patients. The iSAVE enables patient-specific volume and pressure control and incorporates safety features to mitigate cross-contamination between patients and flow changes due to patient interdepe...
Journal of Guidance, Control, and Dynamics, 2017
This paper presents a new approach for the identification of linear state-space models from input... more This paper presents a new approach for the identification of linear state-space models from input–output measurements in the presence of noise. In contrast to the original OKID/ERA algorithm, which works through the observer Markov parameters, the new approach uses the estimated observer output residuals to convert a stochastic identification problem into a virtually deterministic one. A system state-space model and an associated Kalman-filter gain can be then identified. Because the converted problem is virtually deterministic, any deterministic system-identification method can be used. The proposed stochastic-to-deterministic conversion enables these deterministic algorithms to produce the same performance level as the existing stochastic system-identification algorithms.
International Journal of Applied Electromagnetics and Mechanics, 2017
A floating raft system is a special double-layer isolation system aiming to reduce the level of n... more A floating raft system is a special double-layer isolation system aiming to reduce the level of noise and vibration and has been widely applied to many kinds of ships and submarines. It can isolate vibration of hosts and auxiliary machines and reduce the structural noise of ships and submarines effectively. It can also protect the equipments and instruments in ships and submarines from being damaged, and makes them to be operated properly when ships and submarines are subjected to external loads and sudden shocks. However, the floating raft system is generally a flexible structure and it is subject to multiple frequency disturbances. The design of control systems to enhance its isolation performance is an active area of research. This paper presents improvements achieved by using a dynamic step FXLMS controller whose main benefit is to balance convergence speed and steady-state error by making the convergence coefficient vary with time. The mathematical model of the dynamic system to be used in the controller is obtained by the observer/Kalman filter identification (OKID) method. The performance of the new solution (dynamic step size FXLMS with OKID model) is compared with previous work based on a fuzzy controller and a dynamic model identified via the prediction error method. Both simulated and experimental results confirm the validity and the benefits of the approach.
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2016
This paper presents an algorithm for noninvasive estimation of alveolar pressure in mechanically ... more This paper presents an algorithm for noninvasive estimation of alveolar pressure in mechanically ventilated patients who are spontaneously breathing. Continual monitoring of alveolar pressure is desirable to prevent ventilator-induced lung injury and to assess the intrinsic positive end-expiratory pressure (PEEPi), which is a parameter of clinical relevance in respiratory care and difficult to measure noninvasively. The algorithm is based on a physiological model of the respiratory system and, as such, it also provides insight into the respiratory mechanics of the patient under mechanical ventilation. In particular, the algorithm allows one to correctly estimate other clinical parameters of interest such as the patient's respiratory resistance and elastance, even in the presence of PEEPi.
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
The paper presents a study of the identifiability of a lumped model of the cardiovascular system.... more The paper presents a study of the identifiability of a lumped model of the cardiovascular system. The significance of this work from the existing literature is in the potential advantage of using both arterial and central venous (CVP) pressures, two signals that are frequently monitored in the critical care unit. The analysis is done on the system's state-space representation via control theory and system identification techniques. Non-parametric state-space identification is preferred over other identification techniques as it optimally assesses the order of a model, which best describes the input-output data, without any prior knowledge about the system. In particular, a recent system identification algorithm, namely Observer Kalman Filter Identification with Deterministic Projection, is used to identify a simplified version of an existing cardiopulmonary model. The outcome of the study highlights the following two facts. In the deterministic (noiseless) case, the theoretical indicators report that the model is fully identifiable, whereas the stochastic case reveals the difficulty in determining the complete system's dynamics. This suggests that even with the use of CVP as an additional pressure signal, the identification of a more detailed (high order) model of the circulatory system remains a challenging task.
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Papers by Francesco Vicario