Antonio Ferreira

A Dynamical State Space Representation and Performance Analysis of a Feedback-Controlled Rotary Left Ventricular Assist Device

The left ventricular assist device (LVAD) is a mechanical device that can assist an ailing heart in performing its functions. The latest generation of such devices is comprised of rotary pumps which are generally much smaller, lighter, and quieter than the conventional pulsatile pumps. The rotary pumps are controlled by varying the rotor (impeller) speed. If the patient is in a health care facility, the pump speed can be adjusted manually by a trained clinician to meet the patients blood needs. However, an important challenge facing the increased use of these LVADs is the desire to allow the patient to return home. The development of an appropriate feedback controller for the pump speed is therefore crucial to meet this challenge. In addition to being able to adapt to changes in the patients daily activities by automatically regulating the pump speed, the controller must also be able to prevent the occurrence of excessive pumping (known as suction) which may cause collapse of the ventricle. In this paper we will discuss some theoretical and practical issues associated with the development of such a controller. As a first step, we present and validate a state-space mathematical model, based on a nonlinear equivalent circuit flow model, which represents the interaction of the pump with the left ventricle of the heart. The associated model is a six-dimensional vector of time varying nonlinear differential equations. The time variation occurs over four consecutive intervals representing the contraction, ejection, relaxation, and filling phases of the left ventricle. The pump in the model is represented by a nonlinear differential equation which relates the pump rotational speed and the pump flow to the pressure difference across the pump. Using this model, we discuss a feedback controller which adjusts the pump speed based on the slope of the minimum pump flow signal, which is one of the model state variables that can be measured. The objective of the controller is to increase the speed until the envelope of the minimum pump flow signal reaches an extreme point and maintain it afterwards. Simulation results using the model equipped with this feedback controller are presented for two different scenarios of patient activities. Performance of the controller when measurement noise is added to the pump flow signal is also investigated.

A Control System for Rotary Blood Pumps Based on Suction Detection

A control system for rotary ventricular assist devices was developed to automatically regulate the pumping speed of the device to avoid ventricular suction. The control system comprises a suction detector and a fuzzy logic controller (FLC). The suction detector can correctly classify pump flow patterns, using a discriminant analysis (DA) model that combines several indices derived from the pump flow signal, to classify the pump status as one of the following: no suction (NS), moderate suction (MS), and severe suction (SS). The discriminant scores, which are the output of the suction detector, were used as inputs to the FLC. Based on this information, the controller updates pump speed, providing adequate flow and pressure perfusion to the patient. The performance of the control system was tested in simulations over a wide range of physiological conditions, including hypertension, exercise, and strenuous exercising for healthy, sick, and very sick hearts, using a lumped parameter model of the circulatory system coupled with a left ventricular assist device. The controller was able to maintain cardiac output and mean arterial pressure within acceptable physiologic ranges, while avoiding suction, demonstrating the feasibility of the proposed control system.

A rule-based controller based on suction detection for rotary blood pumps

A rule-based controller for rotary ventricular assist devices was developed to automatically regulate the pumping speed of the device without introducing suction in the ventricle. The control approach is based on a discriminant analysis function that detects the occurrence of suction, providing the input for the rule-based controller. This controller has been tested in simulations showing the ability to autonomously adjust pump flow according to the patients level of activity, while sustaining adequate perfusion pressures. The performance of the system (suction detector and controller) was tested for several levels of activity and contractility state of the left ventricle, using a lumped parameter model of the circulatory system coupled with a left ventricular assist device. In all cases, the controller kept cardiac output and mean arterial pressure within acceptable physiologic ranges.

A Robust Reference Signal Generator for Synchronized Ventricular Assist Devices

Ventricular assist devices (VADs) are blood pumps that offer an option to support the circulation of patients with severe heart failure. Since a failing heart has a remaining pump function, its interaction with the VAD influences the hemodynamics. Ideally, the hearts action is taken into account for actuating the device such that the device is synchronized to the natural cardiac cycle. To realize this in practice, a reliable real-time algorithm for the automatic synchronization of the VAD to the heart rate is required. This paper defines the tasks such an algorithm needs to fulfill: the automatic detection of irregular heart beats and the feedback control of the phase shift between the systolic phases of the heart and the assist device. We demonstrate a possible solution to these problems and analyze its performance in two steps. First, the algorithm is tested using the MIT-BIH arrhythmia database. Second, the algorithm is implemented in a controller for a pulsatile and a continuous-flow VAD. These devices are connected to a hybrid mock circulation where three test scenarios are evaluated. The proposed algorithm ensures a reliable synchronization of the VAD to the heart cycle, while being insensitive to irregularities in the heart rate.

Integrated Monitoring of Mola mola Behaviour in Space and Time.

Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m) behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, p<0.001). The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator’s fine-scale behaviour observed over a two weeks in May 2014.

Frequency and Time-Frequency Based Indices For Suction Detection in Rotary Blood Pumps

A new suction detection system for rotary blood pumps used in left ventricular assist devices is presented. The system is based on frequency indices combined with a time-frequency extraction feature algorithm. The frequency based indices can detect the changes in the harmonic and subharmonic energy content of the pump flow signal, when a suction event is occurring. The time-frequency extraction feature algorithm can track variations in the standard deviation of the instantaneous frequency of that signal. These two pieces of information are then combined in a weighted decision system to generate a suction alarm. The proposed system has been tested in simulations, in a mock-loop system, and in-vivo tests and produced very satisfactory results

A Dynamical State Space Representation and Performance Analysis of a Feedback Controlled Rotary Left Ventricular Assist Device

The Left Ventricular Assist Device (LVAD) is a mechanical device that can assist an ailing natural heart in performing its functions. The latest generation of such devices is a rotary-type pump which is generally much smaller, lighter, and quieter than the conventional pulsatile-type pump. The rotary-type pumps are controlled by varying the rotor (impeller) speed. If the patient is in a health care facility, the pump speed can be adjusted manually by a trained clinician. However, an important challenge facing the increased use of these LVADs, is the desire to allow the patient to return home. The development of an appropriate patient adaptive feedback speed controller for the pump is therefore crucial to meet this challenge. In addition to being able to adapt to changes in the patient’s daily activities by automatically regulating the pump speed, the controller must also be able to prevent the occurrence of suction. In this paper we will discuss the theoretical and practical issues associated with the development of such a controller. As a flrst step, we will present a state-space mathematical model, based on a nonlinear equivalent circuit flow model, which represents the interaction of the pump with the left ventricle of the heart. The associated state space model is a 5-dimensional vector of time varying nonlinear difierential equations. The time variation occurs over 4 consecutive intervals representing the contraction, ejection, relaxation, and fllling phases of the left ventricle. The pump in the model is represented by a nonlinear equation which relates the pump rotational speed and the pump flow to the pressure difierence across the pump. Using this model, we will discuss a gradient based feedback controller which increases the pump speed to meet the patient requirements up to the point where suction may occur. At that point the controller will maintain a constant pump speed keeping the gradient of the minimum pump flow at zero. Simulation results using the model equipped with the feedback controller are presented for two cases representing two levels of patient activities. Performance of the controller for noisy measurements of pump blood flow is also investigated. Our results show that such a feedback controller performs very well and is fairly robust against measurements noise.© 2005 ASME

Personalized Modeling for Prediction with Decision-Path Models

Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach.

Marble Cutting By Laser

Through the present work on marble laser cutting, some advantages of this method over the conventional process were ascertained. Several parameters relevant to marble laser cutting have been measured, namely the cutting speed as a function of the thickness of the marble plate and the output power of CO2 Laser.