Closed-Loop Quantitative Verification of Rate-Adaptive Pacemakers

Rate-adaptive pacemakers are cardiac devices able to automatically adjust the pacing rate in patients with chronotropic incompetence, i.e. whose heart is unable to provide an adequate rate at increasing levels of physical, mental or emotional activity. These devices work by processing data from physiological sensors in order to detect the patient’s activity and update the pacing rate accordingly. Rate-adaptation parameters depend on many patient-specific factors, and effective personalisation of such treatments can only be achieved through extensive exercise testing, which is normally intolerable for a cardiac patient. In this work, we introduce a data-driven and model-based approach for the automated verification of rate-adaptive pacemakers and formal analysis of personalised treatments. To this purpose, we develop a novel dual-sensor pacemaker model where the adaptive rate is computed by blending information from an accelerometer, and a metabolic sensor based on the QT interval. Our approach enables personalisation through the estimation of heart model parameters from patient data (electrocardiogram), and closed-loop analysis through the online generation of synthetic, model-based QT intervals and acceleration signals. In addition to personalisation, we also support the derivation of models able to account for the varied characteristics of a virtual patient population, thus enabling safety verification of the device. To capture the probabilistic and non-linear dynamics of the heart, we define a probabilistic extension of timed I/O automata with data and employ statistical model checking for quantitative verification of rate modulation. We evaluate our rate-adaptive pacemaker design on three subjects and a pool of virtual patients, demonstrating the potential of our approach to provide rigorous, quantitative insights into the closed-loop behaviour of the device under different exercise levels and heart conditions

Evaluating On-line Model Checking in UPPAAL-SMC using a Laser Tracheotomy Case Study

On-line model checking is a variant of model checking that evaluates properties of a system concurrently while deployed, which allows overcoming limitations of inaccurate system models. In this paper we conduct a laser tracheotomy case study to evaluate the feasibility of using the statistical model checker UPPAAL-SMC for on-line model checking in a medical application. Development of automatic on-line model checking relies on the precision of the prediction and real-time capabilities as real-time requirements must be met. We evaluate the case study with regards to these qualities and our results show that using UPPAAL-SMC in an on-line model checking context is practical: relative prediction errors were only 2% on average and guarantees could be established within reasonable time during our experiments

Model-Based Analysis of User Behaviors in Medical Cyber-Physical Systems

Human operators play a critical role in various Cyber-Physical System (CPS) domains, for example, transportation, smart living, robotics, and medicine. The rapid advancement of automation technology is driving a trend towards deep human-automation cooperation in many safety-critical applications, making it important to explicitly consider user behaviors throughout the system development cycle. While past research has generated extensive knowledge and techniques for analyzing human-automation interaction, in many emerging applications, it remains an open challenge to develop quantitative models of user behaviors that can be directly incorporated into the system-level analysis. This dissertation describes methods for modeling different types of user behaviors in medical CPS and integrating the behavioral models into system analysis. We make three main contributions. First, we design a model-based analysis framework to evaluate, improve, and formally verify the robustness of generic (i.e., non-personalized) user behaviors that are typically driven by rule-based clinical protocols. We conceptualize a data-driven technique to predict safety-critical events at run-time in the presence of possible time-varying process disturbances. Second, we develop a methodology to systematically identify behavior variables and functional relationships in healthcare applications. We build personalized behavior models and analyze population-level behavioral patterns. Third, we propose a sequential decision filtering technique by leveraging a generic parameter-invariant test to validate behavior information that may be measured through unreliable channels, which is a practical challenge in many human-in-the-loop applications. A unique strength of this validation technique is that it achieves high inter-subject consistency despite uncertain parametric variances in the physiological processes, without needing any individual-level tuning. We validate the proposed approaches by applying them to several case studies

Investigation of Circadian Clock in Peripheral Tissues and Immune-Circadian Interaction in the Domestic Fowl, Gallus Domesticus

The circadian system provides living organisms a means to adapt their internal physiology to constantly changing environmental conditions that exists on our rotating planet, Earth. Clocks in peripheral tissues are referred to as peripheral which may participate in tissue-specific functions. The first step to investigating the circadian regulation in the peripheral tissues of avians was to examine for the presence of avian orthologs of core components of the molecular clock using Quantitative real time (qRTPCR) assays. We investigated the avian spleen for daily and circadian control of core clock genes and regulation of the inflammatory response by the spleen clock. The core clock genes, bmal1, bmal2, per2, per3 and clock displayed both daily and circadian rhythms. Proinflammatory cytokines TNFα, IL-1β, IL-6 and IL-18 exhibited daily and circadian rhythmic oscillations. A differential expression of proinflammatory cytokine induction was observed in the spleen undergoing lipopolysaccharide (LPS)-induced acute inflammation. Exogenous melatonin administration during inflammation seems to enhance some and repress a few inflammatory cytokines, implying that melatonin is pleiotropic molecule. To compare and contrast the role of peripheral clocks in regulating energy balance and reproduction in layer vs. broiler chicken, the visceral adipose tissue (VAT), ovary and hypothalamus were examined for the presence of core clock genes were investigated in these two lines of poultry birds. Quantitative RT-PCR was employed to examine daily control of core clock genes in these three peripheral tissues over a 24hr period. The layer hens exhibit rhythmic oscillations in the mRNA abundance of the core clock genes in the VAT, ovary and the hypothalamus. The hypothalamus and VAT of the broiler hens exhibit rhythmic mRNA abundance of the core clock genes. However, the clock genes in the ovary of the broiler pullets exhibit marked reduction in their amplitude and rhythms over a 24hr period. The broiler hens are prone to poor energy balance, obesity and reproductive capacity. In summary, these data provide evidence for a functional link between the circadian clock and the ovary by determining clock gene regulation under conditions of disrupted or eliminated reproductive function vs. normal reproductive output

Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype

We introduce data assimilation as a computational method that uses machine learning to combine data with human knowledge in the form of mechanistic models in order to forecast future states, to impute missing data from the past by smoothing, and to infer measurable and unmeasurable quantities that represent clinically and scientifically important phenotypes. We demonstrate the advantages it affords in the context of type 2 diabetes by showing how data assimilation can be used to forecast future glucose values, to impute previously missing glucose values, and to infer type 2 diabetes phenotypes. At the heart of data assimilation is the mechanistic model, here an endocrine model. Such models can vary in complexity, contain testable hypotheses about important mechanics that govern the system (eg, nutrition’s effect on glucose), and, as such, constrain the model space, allowing for accurate estimation using very little data

Simplified modeling of implanted medical devices with metallic filamentary closed loops exposed to low or medium frequency magnetic fields

Background and objectives: Electric currents are induced in implanted medical devices with metallic fila-mentary closed loops (e.g., fixation grids, stents) when exposed to time varying magnetic fields, as those generated during certain diagnostic and therapeutic biomedical treatments. A simplified methodology to efficiently compute these currents, to estimate the altered electromagnetic field distribution in the bio-logical tissues and to assess the consequent biological effects is proposed for low or medium frequency fields.Methods: The proposed methodology is based on decoupling the handling of the filamentary wire and the anatomical body. To do this, a circuital solution is adopted to study the metallic filamentary implant and this solution is inserted in the electromagnetic field solution involving the biological tissues. The Joule losses computed in the implant are then used as a forcing term for the thermal problem defined by the bioheat Pennes' equation. The methodology is validated against a model problem, where a reference solution is available.Results: The proposed simplified methodology is proved to be in good agreement with solutions provided by alternative approaches. In particular, errors in the amplitude of the currents induced in the wires re-sult to be always lower than 3%. After the validation, the methodology is applied to check the interactions between the magnetic field generated by different biomedical devices and a skull grid, which represents a complex filamentary wire implant.Conclusions: The proposed simplified methodology, suitable to be applied to closed loop wires in the low to intermediate frequency range, is found to be sufficiently accurate and easy to apply in realistic exposure scenarios. This modeling tool allows analyzing different types of small implants, from coronary and biliary duct stents to orthopedic grids, under a variety of exposure scenarios.(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/

Acquisition of cardiac control parameters from whole vagus nerve recordings

Heart rate varies continuously depending on the amount of activity being performed or the emotional state of an individual. Both branches of the autonomic nervous system work to alter heart rate depending on the needs of the body. While healthy individuals are capable of altering their heart rate, individuals with certain types of heart disease do not have this ability. For these individuals, cardiac pacemakers are used to alter heart rate. Cardiac pacemakers use sensors to determine the pacing frequency for the heart; however, there is no current optimum sensor. In order to discover a better sensor, this study investigated the use of parasympathetic motor activity via the vagus nerve to predict heart rate. Vagus nerve activity and EKG signals were recorded simultaneously; two types of recordings were taken: baseline and altered heart rate recordings achieved by performing bi-lateral carotid artery occlusion. Whole vagus nerve discharges were recorded using small silicone cuff electrodes with platinum contacts. Neural activity and EKG signals obtained from these experiments were filtered for frequency content. After filtering, the vagus motor signal was calculated by using a cross correlation technique introduced by Heetderks. The vagus motor activity was integrated between successive R waves taken from the recorded EKG and correlated with instantaneous heart rate. Consistent, high inverse correlations between integrated vagus motor activity and instantaneous heart rate were found in baseline and occlusion recordings. After obtaining consistent correlations between the integrated vagal motor activity and instantaneous heart rate, a transfer function model was developed using time series analysis methods. The transfer function model whose input was integrated vagus motor activity and whose output was heart rate was capable of predicting heart rate within a 95% confidence interval

Investigation of Circadian Clock in Peripheral Tissues and Immune-Circadian Interaction in the Domestic Fowl, Gallus Domesticus

The circadian system provides living organisms a means to adapt their internal physiology to constantly changing environmental conditions that exists on our rotating planet, Earth. Clocks in peripheral tissues are referred to as peripheral which may participate in tissue-specific functions. The first step to investigating the circadian regulation in the peripheral tissues of avians was to examine for the presence of avian orthologs of core components of the molecular clock using Quantitative real time (qRTPCR) assays. We investigated the avian spleen for daily and circadian control of core clock genes and regulation of the inflammatory response by the spleen clock. The core clock genes, bmal1, bmal2, per2, per3 and clock displayed both daily and circadian rhythms. Proinflammatory cytokines TNFα, IL-1β, IL-6 and IL-18 exhibited daily and circadian rhythmic oscillations. A differential expression of proinflammatory cytokine induction was observed in the spleen undergoing lipopolysaccharide (LPS)-induced acute inflammation. Exogenous melatonin administration during inflammation seems to enhance some and repress a few inflammatory cytokines, implying that melatonin is pleiotropic molecule. To compare and contrast the role of peripheral clocks in regulating energy balance and reproduction in layer vs. broiler chicken, the visceral adipose tissue (VAT), ovary and hypothalamus were examined for the presence of core clock genes were investigated in these two lines of poultry birds. Quantitative RT-PCR was employed to examine daily control of core clock genes in these three peripheral tissues over a 24hr period. The layer hens exhibit rhythmic oscillations in the mRNA abundance of the core clock genes in the VAT, ovary and the hypothalamus. The hypothalamus and VAT of the broiler hens exhibit rhythmic mRNA abundance of the core clock genes. However, the clock genes in the ovary of the broiler pullets exhibit marked reduction in their amplitude and rhythms over a 24hr period. The broiler hens are prone to poor energy balance, obesity and reproductive capacity. In summary, these data provide evidence for a functional link between the circadian clock and the ovary by determining clock gene regulation under conditions of disrupted or eliminated reproductive function vs. normal reproductive output