scholarly journals Combining Physiology-Based Modeling and Evolutionary Algorithms for Personalized, Noninvasive Cardiovascular Assessment Based on Electrocardiography and Ballistocardiography

2022 ◽  
Vol 12 ◽  
Author(s):  
Nicholas Mattia Marazzi ◽  
Giovanna Guidoboni ◽  
Mohamed Zaid ◽  
Lorenzo Sala ◽  
Salman Ahmad ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Mathematical Model ◽  
Blood Pressure Measurement ◽  
Model Parameters ◽  
Cardiovascular Monitoring ◽  
Cardiovascular Parameters ◽  
Physiological Variables ◽  
Novel Approach ◽  
Cardiovascular Assessment ◽  
Parameter Values

Purpose: This study proposes a novel approach to obtain personalized estimates of cardiovascular parameters by combining (i) electrocardiography and ballistocardiography for noninvasive cardiovascular monitoring, (ii) a physiology-based mathematical model for predicting personalized cardiovascular variables, and (iii) an evolutionary algorithm (EA) for searching optimal model parameters.Methods: Electrocardiogram (ECG), ballistocardiogram (BCG), and a total of six blood pressure measurements are recorded on three healthy subjects. The R peaks in the ECG are used to segment the BCG signal into single BCG curves for each heart beat. The time distance between R peaks is used as an input for a validated physiology-based mathematical model that predicts distributions of pressures and volumes in the cardiovascular system, along with the associated BCG curve. An EA is designed to search the generation of parameter values of the cardiovascular model that optimizes the match between model-predicted and experimentally-measured BCG curves. The physiological relevance of the optimal EA solution is evaluated a posteriori by comparing the model-predicted blood pressure with a cuff placed on the arm of the subjects to measure the blood pressure.Results: The proposed approach successfully captures amplitudes and timings of the most prominent peak and valley in the BCG curve, also known as the J peak and K valley. The values of cardiovascular parameters pertaining to ventricular function can be estimated by the EA in a consistent manner when the search is performed over five different BCG curves corresponding to five different heart-beats of the same subject. Notably, the blood pressure predicted by the physiology-based model with the personalized parameter values provided by the EA search exhibits a very good agreement with the cuff-based blood pressure measurement.Conclusion: The combination of EA with physiology-based modeling proved capable of providing personalized estimates of cardiovascular parameters and physiological variables of great interest, such as blood pressure. This novel approach opens the possibility for developing quantitative devices for noninvasive cardiovascular monitoring based on BCG sensing.

scholarly journals Co-Operation with Pre-Operative Cardiovascular Monitoring Amongst Children for Chair Dental General Anaesthesia

2006 ◽  
Vol 88 (2) ◽  
pp. 207-209 ◽  
Author(s):  
Rachel Seed ◽  
Charlotte Boardman ◽  
Mark Davies
Keyword(s):  
Blood Pressure ◽  
Pulse Oximetry ◽  
General Anaesthesia ◽  
Pressure Measurement ◽  
Blood Pressure Measurement ◽  
Cardiovascular Monitoring ◽  
Invasive Blood Pressure ◽  
Non Invasive ◽  
Dental General Anaesthesia ◽  
Invasive Blood Pressure Measurement

INTRODUCTION The Association of Anaesthetists of Great Britain and Ireland (AAGBI) guidelines Recommendations for standards of monitoring during anaesthesia and recovery state that cardiovascular monitoring for induction of general anaesthesia should include pulse oximetry and non-invasive blood pressure measurement, but recognise that young patients may not co-operate sufficiently to allow this. The aim of this study was to look at levels of compliance possible for pulse oximetry and non-invasive blood pressure measurement, in a population known to be unco-operative with therapeutic interventions. PATIENTS AND METHODS A retrospective review of 500 records of patients attending for chair dental general anaesthesia was carried out. It was recorded whether pre-operatively pulse oximetry and non-invasive blood pressure measurement had been allowed in addition to the child's age and sex. RESULTS Of the children, 52% were male and 48% were female. The age range was 2–15 years. Overall, 448 children co-operated with both pulse oximetry and non-invasive blood pressure measurement. Co-operation appeared to increase with increasing age. DISCUSSION Of the children, 90% were co-operative with pre-operative monitoring. It could easily be assumed that many of these children, who are referred for general anaesthesia because they are less co-operative than their peers, would not allow proper pre-operative cardiovascular monitoring. This does not appear to be the case. CONCLUSIONS The majority of children, including the very young, attending for chair dental general anaesthesia, will co-operate sufficiently to allow cardiovascular monitoring during induction of anaesthesia, even though the majority will not tolerate exodontia under local anaesthesia.

Validation of a Mathematical Model for Road Cycling Power

1998 ◽  
Vol 14 (3) ◽  
pp. 276-291 ◽  
Author(s):  
James C. Martin ◽  
Douglas L. Milliken ◽  
John E. Cobb ◽  
Kevin L. McFadden ◽  
Andrew R. Coggan
Keyword(s):  
Mathematical Model ◽  
Measurement System ◽  
Standard Error ◽  
Power Measurement ◽  
Model Parameters ◽  
Model Parameter ◽  
Road Cycling ◽  
Highly Correlated ◽  
Parameter Values ◽  
Measured Power

This investigation sought to determine if cycling power could be accurately modeled. A mathematical model of cycling power was derived, and values for each model parameter were determined. A bicycle-mounted power measurement system was validated by comparison with a laboratory ergometer. Power was measured during road cycling, and the measured values were compared with the values predicted by the model. The measured values for power were highly correlated (R2= .97) with, and were not different than, the modeled values. The standard error between the modeled and measured power (2.7 W) was very small. The model was also used to estimate the effects of changes in several model parameters on cycling velocity. Over the range of parameter values evaluated, velocity varied linearly (R2> .99). The results demonstrated that cycling power can be accurately predicted by a mathematical model.

scholarly journals Development of a semi-distributed hydrological model on a tidal-affected river: application to the Adour catchment, France.

2020 ◽  
Author(s):  
Valentin Mansanarez ◽  
Guillaume Thirel ◽  
Olivier Delaigue ◽  
Benoit Liquet
Keyword(s):  
Hydrological Model ◽  
Potential Evapotranspiration ◽  
River Mouth ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Natural Systems ◽  
Tidal Influence ◽  
Novel Approach ◽  
Spatio Temporal ◽  
Parameter Values

<p>Streamflow estimation from rain events is a delicate exercise. Watersheds are complex natural systems and their response to rainfall events is influenced by many factors. Hydrological rainfall-runoff modelling is traditionally used to understand those factors by predicting discharges from precipitation data. These models are simplified conceptualisations and thus still struggle when facing some particular processes linked to the catchment. Among those processes, the tide influence on river discharges is rarely accounted for in hydrological modelling when estimating streamflow series at river mouth areas. Instead, estimated streamflow series are sometimes corrected by coefficients to account for the tide effect.</p><p>In this presentation, we explored a semi-distributed hydrological model by adapting it to account for tidal-influence in the river mouth area. This model uses observed spatio-temporal rainfall and potential evapotranspiration databases to predict streamflow at gauged and ungauged locations within the catchment. The hydrological model is calibrated using streamflow observations and priors on parameter values to calibrate each model parameters of each sub-catchments. A drift procedure in the calibration process is used to ensure continuity in parameter values between upstream and downstream successive sub-catchments.</p><p>This novel approach was applied to a tidal-affected catchment: the Adour’s catchment in southern France. Estimated results were compared to simulations without accounting for the tidal influence. Results from the new hydrological model were improved at tidal-affected locations of the catchment. They also show similar estimations in tidal-unaffected part of the catchment.</p>

scholarly journals Physical and Mathematical Model of Heart and Cardiovascular System

2020 ◽  
pp. 4-10
Author(s):  
Aditya Kundu ◽  
Ananya Kundu ◽  
Goutam Kumar Kundu
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Mathematical Model ◽  
Cardiovascular System ◽  
Flow System ◽  
Circulatory System ◽  
Activity Level ◽  
System Modelling ◽  
Cardiovascular Parameters ◽  
Piping Systems

The cardiovascular system is modelled as a fluid flow system consisting of networks of pumps and piping systems. A mathematical model relating different cardiovascular parameters was developed. The change in cardiovascular parameters with individuals’ physical activity level, habits and environmental factors was established. The models used to predict how an individual can control the cardiovascular parameters to be healthy and diagnosing problems in the system.Keywords: Blood Pressure; Circulatory system modelling; Heart Rate.

scholarly journals Forecasting the Bladder Tumor Size and Immune Response of a Patient Over the Time Using a Dynamic Mathematical Model

2018 ◽  
Author(s):  
Clara Burgos ◽  
Noemí García-Medina ◽  
David Martínez-Rodríguez ◽  
José-Luis Pontones ◽  
David Ramos ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Immune Response ◽  
Tumor Size ◽  
Model Calibration ◽  
Bladder Tumor ◽  
Tumor Evolution ◽  
Model Parameters ◽  
Single Patient ◽  
Dynamic Mathematical Model ◽  
Parameter Values

Bladder cancer is one of the most common malignant diseases in the urinary system and a highly aggressive neoplasm. The prognosis is not favourable usually and its evolution for particular patients is very difficult to find out. In this paper we propose a dynamic mathematical model that describes the bladder tumor growth and the immune response evolution. This model is customized for a single patient, determining appropriate model parameter values via model calibration. Due to the uncertainty of the tumor evolution, using the calibrated model parameters, we predict the tumor size and the immune response evolution over the next few months assuming three different scenarios: favourable, neutral and unfavourable. In the former, the cancer disappears; in the second a 5mm tumor is expected around the middle of August 2018; in the worst scenario, a 5mm tumor is expected around the end of May 2018. The patient has been cited around June 15th, 2018, to check the tumor size, if it exists.

scholarly journals The Role of Oxygen Intake and Liver Enzyme on The Dynamics of Damaged Hepatocytes: Implications to Ischaemic Liver Injury via A Mathematical Model

2020 ◽  
Author(s):  
Aditi Ghosh ◽  
Claire Onsager ◽  
Leon Arriola ◽  
Andrew Mason ◽  
William Lee ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Liver Injury ◽  
Real Time ◽  
The Body ◽  
Model Parameters ◽  
Oxygen Intake ◽  
Serum Aminotransferase ◽  
Time Dynamics ◽  
Novel Approach ◽  
Time Basis

AbstractIschaemic Hepatitis (IH) or Hypoxic Hepatitis (HH) also known as centrilobular liver cell necrosis is an acute liver injury characterized by a rapid increase in serum aminotransferase. The liver injury typically results from another underlying medical conditions like cardiac failure, respiratory failure and septic shock in which the liver becomes damaged due to deprivation of either blood or oxygen. IH is a potentially lethal condition which is often preventable if diagnosed properly. Unfortunately, mechanism that causes IH are often not well understood, making it difficult to diagnose or accurately quantify the patterns of related biomakers. In most cases, currently the only way to determine a case of IH (i.e., to diagnose it) is to rule out all other possible conditions for other liver injuries. A better understanding of the liver’s response to IH is necessary to aid in its diagnosis, measurement and improve outcomes. The goal of this study, is to identify mechanisms that can alter a few associated biomarkers for reducing density of damaged hepatocytes, and thus reduce chances of IH. To this end, we develop a mathematical model capturing dynamics of hepatocytes in the liver through the rise and fall of associated liver enzymes aspartate transaminase (AST), alanine transaminase (ALT) and lactate dehydrogenase (LDH) related to condition of IH. The model analysis provides a novel approach to predict the level of biomarkers given variations in the systemic oxygen in the body. Using IH patient data in US, novel model parameters are described and then estimated for the first time to capture real time dynamics of hepatocytes in the presence and absence of IH condition. Different scenarios of patient conditions were also analyzed and validated using empirical information. This study and its results may allow physicians to estimate the extent of liver damage in a IH patient based on their enzyme levels and receive faster treatment on real time basis.

Modeling Heart Rate Dynamics in Response to Changes in Exercise Intensity

2015 ◽  
Author(s):  
Michael J. Mazzoleni ◽  
Claudio L. Battaglini ◽  
Brian P. Mann
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Heart Rate ◽  
Heart Rate Response ◽  
Synthetic Data ◽  
Model Parameters ◽  
Nonlinear Mathematical Model ◽  
Heart Rate Dynamics ◽  
Parameter Values ◽  
Good Agreement

This paper develops a nonlinear mathematical model to describe the heart rate response of an individual during cycling. The model is able to account for the fluctuations of an individual’s heart rate while they participate in exercise that varies in intensity. A method for estimating the model parameters using a genetic algorithm is presented and implemented, and the results show good agreement between the actual parameter values and the estimated values when tested using synthetic data.

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