Balázs Benyó

15757116300

Publications - 39

Advances in invasive and non-invasive glucose monitoring: A review of microwave-based sensors

Balázs Benyó J. Geoffrey Chase K. Kovács Ameer B. Alsultani

Publication Name: Sensors and Actuators Reports

Publication Date: 2025-06-01

Volume: 9

Issue: Unknown

Page Range: Unknown

Description:

Effective and continuous glucose monitoring is critical in managing diabetes, which remains a global health challenge affecting millions. Traditional invasive glucose monitoring methods, although accurate, cause discomfort and are unsuitable for frequent measurements necessary for optimal diabetes management. To overcome these limitations, microwave-based sensors have emerged as promising alternatives, providing both invasive and non-invasive monitoring capabilities. This review critically evaluates recent advancements in microwave-based glucose sensors, emphasizing their design methodologies, sensitivity, accuracy, and clinical applicability. By leveraging unique dielectric properties of blood and tissues affected by glucose concentrations, microwave sensors enable precise and potentially pain-free glucose measurements. Despite significant progress, existing sensor technologies face challenges including limited sensitivity ranges, interference from biological tissues, and practical considerations for clinical adoption. This paper aims to guide researchers and healthcare providers by highlighting recent technological innovations, addressing current limitations, and suggesting directions for future research to advance glucose monitoring technologies towards widespread clinical use.

Open Access: Yes

DOI: 10.1016/j.snr.2025.100332

NeuralODE-based Parameter Identification of the Three Chamber Model of the Circulatory System

Balázs Benyó Ákos Antal Bálint Szabó K. Kovács J. Geoffrey Chase Á Szlávecz

Publication Name: Iccc 2025 IEEE 12th International Joint Conference on Cybernetics and Computational Cybernetics Cyber Medical Systems Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 161-166

Description:

In cases of Acute Circulatory Failure, fluid therapy is a commonly used intervention to stabilize heart function. However, the effectiveness of fluid therapy is not directly predictable, and the therapy can also be harmful. Physiological models can be used to predict fluid responsiveness - describing the effectiveness of fluid therapy for the patient - but require solving complex parameter identification problems. The current study aims to develop a Physics Informed Neural Network, specifically a NeuralODE-based parameter identification method for the Three Chamber cardiovascular model, which has the potential to be used to define a novel perfusion marker. The method is developed and validated on a clinical data set collected in model animal experiments.

Open Access: Yes

DOI: 10.1109/ICCC64928.2025.10999147

Comparison of three artificial intelligence methods for predicting 90% quantile interval of future insulin sensitivity of intensive care patients

Balázs Benyó J. Geoffrey Chase Bálint Szabó K. Kovács Omer S. Alkhafaf Ameer B. Alsultani Á Szlávecz B. Paláncz

Publication Name: IFAC Journal of Systems and Control

Publication Date: 2024-12-01

Volume: 30

Issue: Unknown

Page Range: Unknown

Description:

Insulin dosing of hyperglycemic patients in the intensive care unit (ICU) is a complex and nonlinear clinical control problem. Recent model-based glycemic control protocols predict a patient-specific and time-specific future insulin sensitivity distribution, which defines the future patient state in response to insulin and nutrition inputs. The prediction methods provide a 90% confidence interval for a future insulin sensitivity distribution for a given time horizon, making the prediction problem more specific compared to common prediction problems where the aim is to predict the expected value of the given stochastic parameter. This study proposes three alternative artificial intelligence-based insulin sensitivity prediction methods to improve the prediction accuracy and make prediction parameters better fit the clinical requirements. The proposed prediction methods use different neural network models: a classification deep neural network model, a Mixture Density Network model, and a Quantile Regression-based model. A large patient data set was used to create the neural network models, including 2357 patients and 92646 blood glucose measurements from three clinical sites (Christchurch, New Zealand, Gyula, Hungary, and Liege, Belgium). Prediction accuracy was assessed by statistical metrics expressing clinical requirements, as well as via validated in-silico virtual patient simulations comparing the clinical performance of a proven glycaemic control protocol using the alternative prediction methods to assess impact on glycemic control performance and thus the need for these alternative models.

Open Access: Yes

DOI: 10.1016/j.ifacsc.2024.100284

In-Silico Validation of Insulin Sensitivity Prediction by Neural Network-based Quantile Regression

Balázs Benyó J. Geoffrey Chase Bálint Szabó K. Kovács Omer S. Alkhafaf Ameer B. Alsultani Alaa N. Roel Petra Pintár Á Szlávecz B. Paláncz

Publication Name: IFAC Papersonline

Publication Date: 2024-09-01

Volume: 58

Issue: 24

Page Range: 368-373

Description:

High blood glucose levels and stress-induced hyperglycemia are common issues in intensive care units (ICU). Controlling blood glucose levels is crucial but challenging due to patient-specific variability. This challenge was addressed by developing model-based control protocols, which rely on identifying and predicting the patient-specific metabolic state. This study presents the in-silico simulation-based evaluation of a new artificial neural network-based insulin sensitivity (SI) prediction method. The models were trained on a dataset collected during clinical treatment using the stochastic-targeted (STAR) protocol and evaluated by simulating the clinical interventions on virtual patients created from retrospective clinical data. The results show the new models could be safely applied for SI prediction. Furthermore, the adopted method had very similar accuracy in the overall comparison of cohorts, with only minor differences noted in hypoglycemia events.

Open Access: Yes

DOI: 10.1016/j.ifacol.2024.11.065

Cardiovascular Model Identification Using Neural ODE

Balázs Benyó Ákos Antal J. Geoffrey Chase Bálint Szabó K. Kovács Cong Zhou Liam Murphy James Cushway Nicolas Davey Á Szlávecz B. Paláncz

Publication Name: IFAC Papersonline

Publication Date: 2024-09-01

Volume: 58

Issue: 24

Page Range: 374-379

Description:

Acute circulatory failure (ACF) is a clinical syndrome when the heart and circulatory circulation cannot provide adequate blood supply to meet metabolic needs of the organs. ACF affects 30%- 50% of intensive care unit (ICU) patients. Fluid resuscitation is the primary treatment of ACF. However, it fails in a significant proportion (about 50%) of cases due to lack of clinically feasible non-invasive perfusion markers to assess the efficacy of the fluid therapy. Unfortunately, unsuccessful fluid therapy negatively affects patient outcome, increasing ICU length of stay and costs. Recent studies show identifying Stressed Blood Volume (SBV) of the cardiovascular system can be used to assess the potential efficacy of fluid therapy. The development of the diagnostic method requires the identification of the central arterial pressure curve based on the femoral arterial pressure, which is clinically available. This central arterial pressure curve can be used to identify the cardiovascular system parameters. In this study, the main goal was to develop a parameter-identification method for the Tube-load model-based transfer function connecting the femoral and central arterial pressure curve by using the so-called Physics-informed Neural Network methodology, namely the Neural ODE method. The study presents the adaptation of the Neural ODE method to the given parameter identification problem and the validation of the developed identification method. The robustness of the developed identification method was tested and used on a series of measurement data recorded in animal experiments.

Open Access: Yes

DOI: 10.1016/j.ifacol.2024.11.066

Applying NeuralODE-based Cardiovascular Model Identification for Experimental Data Analysis

Balázs Benyó Ákos Antal J. Geoffrey Chase Bálint Szabó K. Kovács Á Szlávecz

Publication Name: Saci 2024 18th IEEE International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 437-442

Description:

Recent model-based diagnostic methods have been found promising to provide non-invasive perfusion markers to assess the efficacy of fluid therapy, the most common treatment method for acute circulatory failure (ACF). The development of these model-based diagnostic methods requires the identification of the central arterial pressure curve based on the femoral arterial pressure. This current study presents improvements of the previously suggested NeuralODE-based identification method by suggesting the use of a physiologically interpretable parameter set of the Tube-load model-based transfer function for the physiological system analysis and suggesting a calculation method decreasing the measurement error-caused uncertainty of the identification parameter, called pulse transfer time.

Open Access: Yes

DOI: 10.1109/SACI60582.2024.10619737

Classification-based deep neural network vs mixture density network models for insulin sensitivity prediction problem

Balázs Benyó J. Geoffrey Chase Bálint Szabó K. Kovács Á Szlávecz B. Paláncz

Publication Name: Computer Methods and Programs in Biomedicine

Publication Date: 2023-10-01

Volume: 240

Issue: Unknown

Page Range: Unknown

Description:

Model-based glycemic control (GC) protocols are used to treat stress-induced hyperglycaemia in intensive care units (ICUs). The STAR (Stochastic-TARgeted) glycemic control protocol – used in clinical practice in several ICUs in New Zealand, Hungary, Belgium, and Malaysia – is a model-based GC protocol using a patient-specific, model-based insulin sensitivity to describe the patient's actual state. Two neural network based methods are defined in this study to predict the patient's insulin sensitivity parameter: a classification deep neural network and a Mixture Density Network based method. Treatment data from three different patient cohorts are used to train the network models. Accuracy of neural network predictions are compared with the current model- based predictions used to guide care. The prediction accuracy was found to be the same or better than the reference. The authors suggest that these methods may be a promising alternative in model-based clinical treatment for patient state prediction. Still, more research is needed to validate these findings, including in-silico simulations and clinical validation trials.

Open Access: Yes

DOI: 10.1016/j.cmpb.2023.107633

Comparison of Three Artificial Intelligence Methods for Predicting 90% Quantile Interval of Future Insulin Sensitivity of Intensive Care Patients

Balázs Benyó J. Geoffrey Chase Bálint Szabó K. Kovács Á Szlávecz B. Paláncz

Publication Name: IFAC Papersonline

Publication Date: 2023-07-01

Volume: 56

Issue: 2

Page Range: 2091-2095

Description:

Three alternative artificial intelligence-based insulin sensitivity prediction methods are compared in this study. Insulin sensitivity prediction is an essential step in calculating the optimal treatment options in model-based glycemic control protocol of insulin-dependent intensive care patients. The prediction methods must predict not only the expected value of the insulin sensitivity for a given time horizon but also the 90% confidence interval making the prediction problem more specific compared to the common prediction problems. All of the proposed prediction methods - proposed in our previous publications - use different neural network models: a classification deep neural network model, a Mixture Density Network based model, and a Quantile regression based model. The patent data set used for the development and accuracy assessment is from 3 clinical ICU cohorts, including 820 treatment episodes of 606 patients and 68,631 hours of treatment. To evaluate the efficacy of the prediction in the context of clinical requirements, three metrics are used Success rate, Interval ratio, and I-Score are applied.

Open Access: Yes

DOI: 10.1016/j.ifacol.2023.10.1110

Modeling the Correlation of Human Vertebral Body Volumes

Balázs Benyó P. Somogyi Bálint Szabó K. Kovács Sándor Bazsó Á Szlávecz Árpád Viola

Publication Name: IFAC Papersonline

Publication Date: 2023-07-01

Volume: 56

Issue: 2

Page Range: 9030-9035

Description:

Anatomical parameters of the human body strongly correlate with each other. Modelling these dependencies enables the creation of a realistic anatomical human body model that can be parameterized. Such a model can be used for several diagnostic processes to identify abnormalities or even give guidance in surgical interventions. This paper proposes a probabilistic model describing the dependencies between the vertebral body volumes of humans from the Caucasian human race. As demonstrated, the proposed model can accurately describe the relationship between the vertebral body volumes and is used for the prediction of an unknown vertebral volume based on a known one. The probabilistic model is created by using the CT segmentation of 37 patients.

Open Access: Yes

DOI: 10.1016/j.ifacol.2023.10.133

Increasing Patient Specificity of the Recurrent Neural Network Based Insulin Sensitivity Prediction by Transfer Learning

Balázs Benyó J. Geoffrey Chase Bálint Szabó K. Kovács Á Szlávecz B. Paláncz

Publication Name: Ines 2022 26th IEEE International Conference on Intelligent Engineering Systems 2022 Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 27-32

Description:

Insulin therapy is a frequently applied treatment in intensive care to normalize the patient's blood glucose level increased by stress-induced hyperglycaemia. This therapy is generally referred to as Tight Glycaemic Control (TGC). The STAR (Stochastic-TARgeted) protocol is a TGC which uses the patient's insulin sensitivity (SI) as a key parameter to describe the patient's actual state. Prediction of the future patient's state, i.e. prediction of the patient's future SI value, is a crucial step of the protocol currently implemented by using the so-called Intensive Care INsulin Glucose (ICING) model of the human glucose-insulin system and an associated stochastic model. In our previous studies, we have shown that the Recurrent Neural Network (RNN) models are efficient alternative methods of SI prediction. In this paper, we suggest applying the so-called transfer learning technique to further enhance the accuracy of the SI prediction by using the SI history of the current patient. The paper presents the proposed methodology for applying transfer learning in SI prediction and the evaluation of the method's accuracy by comparing the outcomes with the currently applied solution. Insilico validation using real patients' data is involved in this validation.

Open Access: Yes

DOI: 10.1109/INES56734.2022.9922645

Artificial Intelligence Based Insulin Sensitivity Prediction for Personalized Glycaemic Control in Intensive Care

Balázs Benyó J. Geoffrey Chase Bálint Szabó K. Kovács Yahia Anane Á Szlávecz B. Paláncz

Publication Name: IFAC Papersonline

Publication Date: 2020-01-01

Volume: 53

Issue: 2

Page Range: 16335-16340

Description:

Stress-induced hyperglycaemia is a frequent complication in the intensive therapy that can be safely and efficiently treated by using the recently developed model-based tight glycaemic control (TGC) protocols. The most widely applied TGC protocol is the STAR (Stochastic-TARgeted) protocol which uses the insulin sensitivity (SI) for the assessment of the patients state. The patient-specific metabolic variability is managed by the so-called stochastic model allowing the prediction of the 90% confidence interval of the future SI value of the patients. In this paper deep neural network (DNN) based methods (classification DNN and Mixture Density Network) are suggested to implement the patient state prediction. The deep neural networks are trained by using three years of STAR treatment data. The methods are validated by comparing the prediction statistics with the reference data set. The prediction accuracy was also compared with the stochastic model currently used in the clinical practice. The presented results proved the applicability of the neural network based methods for the patient state prediction in the model based clinical treatment. Results suggest that the methods' prediction accuracy was the same or better than the currently used stochastic model. These results are the initial successful step in the validation process of the proposed methods which will be followed by in-silico simulation trials.

Open Access: Yes

DOI: 10.1016/j.ifacol.2020.12.659

Finite Element Simulation Based Analysis of Valve-sparing Aortic Root Surgery

Tamás Umenhoffer Balázs Benyó P. Somogyi K. Kovács Róbert Nagy Bernhard Laufer Anikó Kubovje Á Szlávecz Tamás Szerafin

Publication Name: IFAC Papersonline

Publication Date: 2020-01-01

Volume: 53

Issue: 2

Page Range: 16037-16042

Description:

The valve-sparing aortic root surgery is frequently used in the treatment of aortic root enlargement or aortic root aneurysm. The currently used common surgical practice assumes that the valve leaflets are distributed evenly around the circle defined by the aorta wall which is frequently a false assumption according to hart anatomy studies. A finite element simulation based method is proposed in this study for the analysis of the alternative surgical outcomes of the valve-sparing aortic root surgery. The simulation methods allow the definition of the aortic valve leaflet commissure positions and the diameter of the graft used to replace the aortic root. The suggested methods are able to estimate and quantitatively compare the hemodynamic functions and the robustness of the aortic valve functions. The corresponding modeling environment makes possible the easy definition of the patient specific aortic root model that is used as an input of the simulation. The initial validation of the simulation method was done by a real patient data based simulation study. These results suggest that the currently used surgical practice can be improved.

Open Access: Yes

DOI: 10.1016/j.ifacol.2020.12.409

Extension of a Glycaemic Control Medical Application with New Functions and Ergonomic User Interface Elements

Mihaela Lascu Balázs Benyó K. Kovács Brigitte Beatrix Schweisthal Á Szlávecz

Publication Name: 2018 13th International Symposium on Electronics and Telecommunications Isetc 2018 Conference Proceedings

Publication Date: 2018-12-19

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The human body is composed of numerous highly complex metabolic processes. Abnormal variation of the blood glucose concentration is a common complication in the intensive care units. This paper presents a model-based method of glycaemic control and a medical application implementing the glycaemic control protocol. The principal cases were to extend the functionality of the application in order to automatically create multiple episodes for a patient already in the database of the application and an accessibly view for previous treatments calculation. These functions are very helpful and convenient because allow to the clinicians to have new measurements and a treatment calculation without entering the data of the patient again in the system. The visualization of previous treatments can be efficiently used to define optimized dosing for the subsequent treatment period. The paper concludes with the results of the extension of the medical application.

Open Access: Yes

DOI: 10.1109/ISETC.2018.8583885

Initial value selection of the model parameters in the curve fitting phase of the dynamic SPECT imaging

Balázs Benyó P. Somogyi G. Hesz K. Kovács Zsófia Barna Á Szlávecz

Publication Name: IFAC Papersonline

Publication Date: 2018-01-01

Volume: 51

Issue: 27

Page Range: 241-246

Description:

The dynamic SPECT (Single Photon Emission Computed Tomography) reconstruction algorithm developed in our prior work reconstructs the parameters of the time activity curve for each image voxel directly from the projection images. In each iterations of the SPECT reconstruction beyond the static 3D MLEM (Maximum Likelihood Expectation Maximization) step, the algorithm performs a fitting process for each voxel in order to estimate the parameters describing the function of the examined organ considering that the time frames are not independent from each other. In real cases the fitted curve is nonlinear function of these parameters, it is usually described as the sum of exponential functions. In order to estimate the parameters properly, an iterative root-finding method is applied. In the current study the Newton-Raphson method is used. The selection of a proper initial value for the root-finding method is critical in order to achieve convergence of the fitting process. If the initial guess is not appropriate, the root-finding algorithm can diverge or converge to an inappropriate parameter set that can result in unacceptable reconstructed parameters. This affects then the subsequent MLEM iterations, also neighboring voxels and breaks the reconstruction. In this work we investigated different methods to calculate the initial values of the fitting process and evaluated the reconstructed parameter set of the dynamic SPECT reconstruction algorithm. Three different methods are investigated, one that uses the fitted parameters of the previous MLEM iteration, one that is based on the sum of the geometrical series of the exponentials and one that calculates the best guess using both methods. The three methods were compared by benchmark reconstruction cases using a mathematical phantom. In each reconstruction different initial value selection method was applied then the time activity curves of the voxels belonging to the same tissue were statistically evaluated using the reconstructed parameters. In the study no significant differences were found in the mean value of the reconstructed parameters. The standard deviation of the parameters was similar between the two simple approaches, however, the combination of the methods resulted in better statistical performance.

Open Access: Yes

DOI: 10.1016/j.ifacol.2018.11.635

Safe and secure implementation of the global platform conform infrastructure supporting the customer centric model based ecosystem

Balázs Benyó G. Fördös K. Kovács B. Sodor A. Vilmos

Publication Name: Ines 2016 20th Jubilee IEEE International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2016-08-26

Volume: Unknown

Issue: Unknown

Page Range: 131-140

Description:

Global Platform (GP) as a cross industry, nonprofit association develops and publishes specifications promoting secure deployment and management of multi-Application environments of smart card technology based applications and ensuring their interoperability. The GP specifications define the business and technological processes and the associated security requirements. This publication introduces the design and development of a fully functioning smart card application management infrastructure implementing all the related GP processes and corresponding security requirements. The infrastructure supports all the phases of the application life cycle and all the partners in the ecosystem. The system is tested by several trials and certified by independent security assessment.

Open Access: Yes

DOI: 10.1109/INES.2016.7555107

Investigation of 3D SPECT reconstruction with multi-energy photon emitters 1

Balázs Benyó G. Hesz K. Kovács Á Szlávecz

Publication Name: IFAC Papersonline

Publication Date: 2015-09-01

Volume: 28

Issue: 20

Page Range: 30-35

Description:

Parallel projection based Single Emission Computed Tomography is a widely used nuclear imaging technique. Non-homogeneous attenuation medium and the distance dependent spacial resolution (DDSR) of the parallel imaging cause serious artefacts during image reconstruction. Both effects are dependent on the energy of gamma photons used for imaging. In this paper an efficient parallel reconstruction algorithm is introduced that is executed on the Graphics Processing Unit. The aim of the presented study was to investigate the possibilities of reconstruction techniques when multi-energy photon emitters are used. An analytical 3D projector with attenuation and detector response modelling was used to generate projection sets for Gallium-67 isotope studies. Data were reconstructed from one photopeak only using the corresponding attenuation map. The projection data sets were added together and reconstructed using average attenuation and DDSR compensation values as well as simulating every photopeak individually. The third combined reconstruction technique was using every projection set as separate measurement. In this study we showed that all three strategies result in similar image quality, however the average attenuation correction method is computationally less demanding.

Open Access: Yes

DOI: 10.1016/j.ifacol.2015.10.110

Altered blood glucose dynamics during and after anhepatic phase of liver transplantation: A model-based approach

Balázs Benyó J. Geoffrey Chase Jozsef Homlok Paul Docherty K. Kovács

Publication Name: Ines 2013 IEEE 17th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2013-12-12

Volume: Unknown

Issue: Unknown

Page Range: 65-68

Description:

During liver transplantation (LT) the glucose metabolism is effected by a crucial disturbance. The blood glucose level is extremely hard to control by conventional clinical protocols during this phase. Model based approach can enhance the blood glucose control during the anhepatic phase (absence of liver) and post-anhepatic phase. The physiological constants of validated clinical metabolic model were slightly modified based on previous studies. The model fitting errors and the sufficient capture of the blood glucose (BG) dynamic evinced the applicability of the model. However the sufficient per-patient estimation of endogenous production could more enhance the performance of the model based BG prediction. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2013.6632784

Video based urban traffic analysis in signalized intersections

Balázs Benyó Jozsef Homlok K. Kovács

Publication Name: Ines 2011 15th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2011-08-22

Volume: Unknown

Issue: Unknown

Page Range: 319-324

Description:

Nowadays it is a frequent problem that, the infrastructure-development of land transportation comes up against space limits in many cases, moreover the growth of traffic doesn't slack up. This is particularly typical for urban traffic, effecting traffic jams, lags; not to mention the problem of air pollution. In this case the requirements of sustainable development can be satisfied by the optimization of the existing infrastructure. This procedure always begins by observing, collecting and processing information, followed by model creation. In the next step the identified model will help us to analyze even the most extreme situations through different simulation environments and to prepare different traffic analyses. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2011.5954766

Near Field Communication technology: Contactless applications in mobile environment

Balázs Benyó

Publication Name: 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2007

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: 175-188

Description:

StoLPaN, a pan-European consortium of companies, universities and user groups co-funded by the European Commission (EU), Information Society Technologies (IST) Programme aims to define open commercial and technical frameworks for the remote management of NFC-enabled (NFC: Near Field Communication) services on mobile devices. These frameworks will facilitate the deployment of NFC-enabled mobile applications across a wide range of vertical markets, regardless of the phone type and the nature of the services required. This paper introduces the application opportunities of the NFC technology, the business aspects of the NFC based service development and the technical infrastructure implementing the core of the NFC-enabled services.

Open Access: Yes

DOI: DOI not available

Computer-aided analysis of phisiological systems

Balázs Benyó

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2007-12-01

Volume: 4

Issue: 4

Page Range: 55-68

Description:

This paper presents the recent biomedical engineering research activity of the Medical Informatics Laboratory at the Budapest University of Technology and Economics. The research projects are carried out in the fields as follows: Computer aided identification of physiological systems; Diabetic management and blood glucose control; Remote patient monitoring and diagnostic system; Automated system for analyzing cardiac ultrasound images; Single-channel hybrid ECG segmentation; Event recognition and state classification to detect brain ischemia by means of EEG signal processing; Detection of breathing disorders like apnea and hypopnea; Molecular biology studies with DNA-chips; Evaluation of the cry of normal hearing and hard of hearing infants.

Open Access: Yes

DOI: DOI not available

NFC applications and business model of the ecosystem

Balázs Benyó L. Kutor K. Kovács A. Vilmos

Publication Name: 2007 16th Ist Mobile and Wireless Communications Summit

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

StoLPaN, a pan-European consortium of companies, universities and user groups co-funded by the European Commission (EU), Information Society Technologies (IST) Programme aims to define open commercial and technical frameworks for the remote management of NFC-enabled services on mobile devices. These frameworks will facilitate the deployment of NFC-enabled mobile applications across a wide range of vertical markets, regardless of the phone type and the nature of the services required. This paper introduces the business aspects of the NFC based service development and the technical infrastructure implementing the core of the NFC-enabled services.

Open Access: Yes

DOI: 10.1109/ISTMWC.2007.4299324

The design of NFC based applications

Balázs Benyó L. Kutor K. Kovács A. Vilmos

Publication Name: Ines 2007 11th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: 277-280

Description:

StoLPaN, a pan-European consortium of companies, universities and user groups co-funded by the European Commission (EU), Information Society Technologies (IST) Programme aims to define open commercial and technical frameworks for the remote management of NFC-enabled services on mobile devices. These frameworks will facilitate the deployment of NFC-enabled mobile applications across a wide range of vertical markets, regardless of the phone type and the nature of the services required. This paper introduces the business aspects of the NFC based service development and the technical infrastructure implementing the core of the NFC-enabled services. ©2007 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2007.4283711

Analysis of temporal patterns of physiological parameters

Balázs Benyó

Publication Name: Neural Networks in Healthcare Potential and Challenges

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 284-316

Description:

This chapter deals with the analysis of spontaneous changes occurring in two physiological parameters: the cerebral blood flow and respiration. Oscillation of the cerebral blood flow is a common feature in several physiological or pathophysiological states and may significantly influence the metabolic state of the brain. Our goal was to characterize the temporal blood flow pattern before, during, and after the development of CBF oscillations. Investigation of this phenomenon may not only clarify the underlying regulatory mechanisms and their alterations under certain conditions but also lead to the development of novel clinical diagnostic tools for early identification of developing cerebrovascular dysfunction in pathophysiological states such as brain trauma or stroke. A disturbance in normal breathing may occur in several nervous and physical diseases. In the present study, we introduce a reliable online method which is able to recognize abnormal sections of respiration, that is, the most common breathing disorder, the sleep apnea syndrome, based on a single time signal, the nasal air flow. There are several common features of the above problems and signals under investigation that imply similar solutions. The chapter introduces the systematic way of selecting proper feature extraction method and optimal classification procedure. The introduced approach can be generalized for the analysis of similar time series featuring physiological parameters. © 2006, Idea Group Inc.

Open Access: Yes

DOI: 10.4018/978-1-59140-848-2.ch013

Robust blood-glucose control using Mathematica

Balázs Benyó László Török L. Kovács Zoltán Benyó B. Paláncz

Publication Name: Annual International Conference of the IEEE Engineering in Medicine and Biology Proceedings

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 451-454

Description:

A robust control design on frequency domain using Mathematica is presented for regularization of glucose level in Type I diabetes persons under intensive care. The method originally proposed under Mathematica by Helton and Merino, [1] - now with an improved disturbance rejection constraint inequality - is employed, using the three-state minimal patient model of [2]. The robustness of the resulted high-order linear controller is demonstrated by nonlinear closed loop simulation in state-space, in case of standard meal disturbances and is compared with H∞ design implemented with the mu-toolbox of Matlab. The controller designed with model parameters represented the most favorable plant dynamics from the point of view of control purposes, can operate properly even in case of parameter values of the worst-case scenario. ©2006 IEEE.

Open Access: Yes

DOI: 10.1109/IEMBS.2006.259916

Design and implementation of Enum-based services

F. Hatwágner T. Heckenast Á Varga N. Varjasi Balázs Benyó K. Kovács

Publication Name: Journal of Universal Computer Science

Publication Date: 2006-11-23

Volume: 12

Issue: 9

Page Range: 1128-1138

Description:

ENUM is a technology based on a procedure that assigns a sequence of traditional telephone numbers to Internet domain names. It specifies a rule that makes it possible to relate a domain to a telephone number without any risk of ambiguity. This domain can then be used to identify various communication services like fax, mobile phone numbers, voice-mail systems, e-mail addresses, IP telephone addresses, web pages, OPS coordinates, call diverts or unified messaging. In our paper we deal with three main problem areas in connection with the business model of the ENUM service and with the introduction of new services, i.e. the questions of tariffs, legal regulations and financial return. For the ENUM procedure to spread out in use specific services have to be implemented that can exploit the advantages of the ENUM and efficient methods have to be elaborated to base existing services on ENUM. We will outline the two new services invented by our group and that we have implemented in our project. © J.UCS.

Open Access: Yes

DOI: DOI not available

Classification of Time Series Using Singular Values and Wavelet Subband Analysis with ANN and SVM Classifiers

Balázs Benyó P. Somogyi B. Paláncz

Publication Name: Journal of Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2006-07-01

Volume: 10

Issue: 4

Page Range: 498-503

Description:

Oscillation of cerebral blood flow (CBF) in physiological or pathophysiological brain states is common, therefore it is promising to identify cerebral circulation disorders based on CBF signal classification. To characterize temporal blood flow patterns, we applied two feature extractions, spectral matrix and wavelet subband analysis. To distinguish between different physiological states, two different classifications have been developed – the radial basis function-based neural network and a support vector classifier with a Gaussian kernel. Feature extraction and classification are evaluated and their efficiency compared. Calculation was done using Mathematica 5.1 and its Wavelet Application.

Open Access: Yes

DOI: 10.20965/jaciii.2006.p0498

Classification of time series via wavelet subband analysis using support vector machine classifier

Balázs Benyó B. Paláncz

Publication Name: Periodica Polytechnica Electrical Engineering

Publication Date: 2006-01-01

Volume: 50

Issue: 1-2

Page Range: 129-140

Description:

An improved feature extraction method has been developed for classification and identification of time series, in case of the number of the experiments are considerably less than that of the samples in time series. The method based on the subband analysis of the wavelet transformation of the time signals, provides lower dimension feature vectors as well as much more robust kernel-based classifier than the traditional wavelet-based feature extraction method does. The application of this technique is illustrated by the classification of cerebral blood flow oscillation using support vector classifier with Gaussian kernel. The computations were carried out with Mathematica 5.1 and its Wavelet Application.

Open Access: Yes

DOI: DOI not available

In search of the nature of specific nucleic acid-protein interactions

Balázs Benyó J. C. Biro Zoltán Benyó C. Sansom

Publication Name: Acta Physiologica Hungarica

Publication Date: 2005-06-23

Volume: 92

Issue: 1

Page Range: 1-10

Description:

The theory of "codon-amino acid coevolution" was first proposed by Woese in 1967. It suggests that there is a stereochemical matching - that is, affinity - between amino acids and certain of the base triplet sequences that code for those amino acids. We have constructed a Common Periodic Table of Codons and Amino Acids, where the Nucleic Acid Table showed perfect axial symmetry for codons and the corresponding Amino Acid Table also displayed periodicity regarding the biochemical properties (charge and hydrophobicity) of the 20 amino acids and the position of the stop signals. The Table indicates that the middle (2nd) amino acid in the codon has a prominent role in determining some of the structural features of the amino acids. The possibility that physical contact between codons and amino acids might exist was tested on restriction enzymes. Many recognition site-like sequences were found in the coding sequences of these enzymes and as many as 73 examples of codon-amino acid co-location were observed in the 7 known 3D structures (December 2003) of endonuclease-nucleic acid complexes. These results indicate that the smallest possible units of specific nucleic acid-protein interaction are indeed the stereochemically compatible codons and amino acids. © 2005 Akadémiai Kiadó.

Open Access: Yes

DOI: 10.1556/APhysiol.92.2005.1.1

Novel communication services based on ENUM technology

F. Hatwágner T. Heckenast Á Varga N. Varjasi Balázs Benyó K. Kovács

Publication Name: Ines 05 IEEE 9th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2005-01-01

Volume: 2005

Issue: Unknown

Page Range: 217-220

Description:

ENUM is the short name for a protocol for connecting resources of telecommunication and the Internet to one another. It specifies a rule that makes it possible to relate a domain to a telephone number without any risk of ambiguity. This domain can then be used to identify various communication services like fax, mobile radio, voice-mail systems, e-mail addresses, IP telephony addresses, web pages, GPS coordinates, call diverts or unified messaging. Several countries in the world examine the possibilities of the use of ENUM in national trials. Recently two Hungarian universities and an Internet service provider established a research project aiming the development of ENUM based communication services. In Hungary we have to deal not only with the questions of creating and providing the technological background, but also with the business aspects of ENUM based service development. The article will firstly give an overview about the ENUM itself. Then it will deal with ENUM services and business models. After that we discuss the situation of ENUM in different European countries. It will present the planned and accomplished ENUM based services in these countries. Then we are going to give the aims of the project in Hungary, which is led by the Szechenyi Istvan University in Gy6r. In setting these aims we can rely on the projects of other countries, and learn from them. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2005.1555160

Classification of time series using singular values and wavelet subband analysis with ANN and SVM classifiers

Balázs Benyó P. Somogyi Péter Várady B. Paláncz

Publication Name: Ines 05 IEEE 9th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2005-01-01

Volume: 2005

Issue: Unknown

Page Range: 239-243

Description:

Oscillation of the cerebral blood flow (CBF) is a common feature in several physiological or pathophysiological states of the brain. It is promising to identify the disorders of the cerebral circulation based on the classification of CBF signals. In order to distinguish between different physiological states, two different classification methods have been developed; a Radial Basis Function based Neural Network and a Support Vector Classifier with Gaussian kernel. In order to describe the temporal blood flow patterns, two feature extraction procedures were applied; spectral matrix and wavelet subband analysis. These feature extraction and classification methods are evaluated and their efficiencies are compared. The computations were carried out with Mathematica 5.1 and its Wavelet Application. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2005.1555165

Characterization of cerebral blood flow oscillations using different classification methods

Balázs Benyó P. Somogyi Zoltán Benyó B. Paláncz

Publication Name: IFAC Proceedings Volumes IFAC Papersonline

Publication Date: 2005-01-01

Volume: 16

Issue: Unknown

Page Range: 214-219

Description:

Oscillation of the cerebral blood flow (CBF) is a common feature in several physiological or pathophysiological states of the brain. It is a promising opportunity to identify the disorders of the cerebral circulation based on the classification of CBF signals. Three classification models are developed with different heuristic in order to carry out the systematic classification based on a problem specific feature extraction. The efficiency of the selected classification methods are evaluated and compared. Copyright © 2005 IFAC.

Open Access: Yes

DOI: 10.3182/20050703-6-cz-1902.02150

Reconstruction of myocardial short-scan SPECT images

Balázs Benyó Á Szlávecz Péter Várady Tamás Bükki

Publication Name: Ines 05 IEEE 9th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2005-01-01

Volume: 2005

Issue: Unknown

Page Range: 37-41

Description:

In myocardial perfusion SPECT imaging the effect of photon attenuation may introduce artifacts in the reconstructed image due to the highly non-uniform distribution of tissue in the thorax region, potentially resulting in false-positive interpretations. It was the general consideration that the adequate compensation of photon attenuation requires, that the emission data be measured at projection angles over 2π in the case of the attenuation medium is inhomogeneous. The reduction of the scanning angle in SPECT imaging may be desirable because it can reduce scanning time and thereby minimize patient-motion and other artifacts. In SPECT myocardial imaging emission data is measured historically at projection angles over π from the right anterior oblique (RAO) to the left posterior oblique (LPO). This configuration results in better image contrast and, in some cases, betters spatial resolution. However, in this case the reconstructed image may suffer more severely from geometric distortion than 2π angular sampling. It has been proven recently in analytical computer simulation studies that the data function over 2π in SPECT with non-uniform attenuation contains redundant information; therefore the scanning angle theoretically can be reduced from 2π to π without loss of information. In this study our goal was to investigate how the various short-scan SPECT scheme configurations works in a real myocardial SPECT imaging system with highly inhomogeneous attenuating medium using attenuation correction. The measured projection images were reconstructed using the Maximum Likelihood Expectation Maximization algorithm with attenuation correction. The reconstructed slices of the various short-scan configurations and the full-scan slices were compared by a cardiac stress/rest software package. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2005.1555127

Filtering and contrast enhancement on subtracted direct digital angiograms

Balázs Benyó L. Nagy

Publication Name: Annual International Conference of the IEEE Engineering in Medicine and Biology Proceedings

Publication Date: 2004-12-01

Volume: 26 II

Issue: Unknown

Page Range: 1533-1536

Description:

This paper presents the results of a research related to medical image subtraction algorithms. The selected area is of direct digital X-Ray angiography, where subtraction algorithms are the basis of most acquisition and reviewing protocols. The goal of this research is to analyze the currently existing image subtraction algorithms and to propose a new approach based on the experienced limitations, respectively to develop a new imaging technique that allows both contrast agent and radiation dose reduction. The enhancement of the subtraction algorithms is targeted by two means: a) noise reduction on image frames, b) identification of contrast agent injected regions. Both aspects will be studied based on the analysis of the spatio-temporal signal variation that image pixel intensities represent, therefore the resulting algorithm can not be used real time during image acquisition, but as a post processing technique during review. The temporal variation of pixel intensities was then analyzed and a patter check was followed to identify pixels being part of a contrast agent injected region. This information was used to highlight regions of interest and to increase the contrast in poorly injected areas.

Open Access: Yes

DOI: DOI not available

Characterization of the temporal pattern of cerebral blood flow oscillations

Gábor Lenzsér Balázs Benyó B. Paláncz

Publication Name: IEEE International Conference on Neural Networks Conference Proceedings

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 2467-2470

Description:

Oscillation of the cerebral blood flow (CBF) is a common feature in several physiological or pathophysiological states of the brain. It is a promising opportunity to identify the state of the brain based on the classification of CBF signals. In order to carry out classification of the time signals, a feature vector has been extracted to characterize the signals. Unsupervised classification showed that the extracted feature vector is an acceptable representation of the time signals. It also turned out that the difference between normal signal and a signal indicating drug injection effect is significant, and much more dominant than the difference between signals of the right and left brain sides. For the signal classification an Artificial Neural Network (ANN) model based on supervised backpropagation network has been developed and successfully applied.

Open Access: Yes

DOI: 10.1109/IJCNN.2004.1381016

Codes in the codons: Construction of a codon/amino acid periodic table and a study of the nature of specific nucleic acid - Protein interactions

Balázs Benyó J. C. Biro Zoltán Benyó

Publication Name: Annual International Conference of the IEEE Engineering in Medicine and Biology Proceedings

Publication Date: 2004-12-01

Volume: 26 IV

Issue: Unknown

Page Range: 2860-2863

Description:

The theory of "codon-amino acid coevolution" was first proposed by Woese in 1967. It suggests that there is a stereochemical matching - that is, affinity - between amino acids and certain of the base triplet sequences that code for those amino acids. We have constructed a Common Periodic Table of Codons and Amino Acids, where the Nucleic Acid Table showed perfect axial symmetry for codons and the corresponding Amino Acid Table also displayed periodicity regarding the biochemical properties (charge and hydrophobicity) of the 20 amino acids and the position of the stop signals. The Table indicates that the middle (2nd) amino acid in the codon has a prominent role in determining some of the structural features of the amino acids. The possibility that physical contact between codons and amino acids might exist was tested on restriction enzymes. Many recognition site-like sequences were found in the coding sequences of these enzymes and as many as 73 examples of codon - amino acid co-location were observed in the 7 known 3D structures (December 2003) of endonuclease-nucleic acid complexes. These results indicate that the smallest possible units of specific nucleic acid - protein interaction are indeed the stereochemically compatible codons and amino acids.

Open Access: Yes

DOI: DOI not available

A fully symbolic design and modeling of nonlinear glucose control with Control System Professional Suite (CSPS) of Mathematica

Balázs Benyó L. Kovács Zoltán Benyó B. Paláncz

Publication Name: Acta Physiologica Hungarica

Publication Date: 2004-09-09

Volume: 91

Issue: 2

Page Range: 147-156

Description:

In this case study a fully symbolic design and modeling method are presented for blood glucose control of diabetic patients under intensive care using Mathematica. The analysis is based on a modified two-compartment model proposed by Bergman et al. (2). The applied feedback control law decoupling even the nonlinear model leads to a fully symbolic solution of the closed loop equations. The effectivity of the applied symbolic procedures being mostly built-in the new version of Control System Professional Suite (CSPS) Application of Mathematica have been demonstrated for controller design in case of a glucose control for treatment of diabetes mellitus and also presented for a numerical situation described in Juhász (8). The results are in good agreement with the earlier presented symbolic-numeric analysis by Benyó et al. (1).

Open Access: Yes

DOI: 10.1556/APhysiol.91.2004.2.6

Biomedical Engineering Education and Related Research Activity in Hungary

Balázs Benyó P. Somogyi L. Kovács L. Szilágyi Zoltán Benyó Péter Várady

Publication Name: Annual International Conference of the IEEE Engineering in Medicine and Biology Proceedings

Publication Date: 2003-12-01

Volume: 4

Issue: Unknown

Page Range: 3533-3535

Description:

Biomedical Engineering is a relatively new interdisciplinary science. This paper presents the biomedical engineering activity, which is carried out at Budapest University of Technology and Economics and its partner institutes. In the first part the main goals and the curriculum of the Biomedical Engineering ducation Program (BMEEP) is presented. The second part of the paper summarizes the most important biomedical engineering researches carried out mostly in the Biomedical Engineering Laboratory of our university.

Open Access: Yes

DOI: DOI not available

A common periodic table of codons and amino acids

Balázs Benyó G. Fördös J. C. Biro Á Szlávecz T. Micsik Zoltán Benyó C. Sansom

Publication Name: Biochemical and Biophysical Research Communications

Publication Date: 2003-06-27

Volume: 306

Issue: 2

Page Range: 408-415

Description:

A periodic table of codons has been designed where the codons are in regular locations. The table has four fields (16 places in each) one with each of the four nucleotides (A, U, G, C) in the central codon position. Thus, AAA (lysine), UUU (phenylalanine), GGG (glycine), and CCC (proline) were placed into the corners of the fields as the main codons (and amino acids) of the fields. They were connected to each other by six axes. The resulting nucleic acid periodic table showed perfect axial symmetry for codons. The corresponding amino acid table also displaced periodicity regarding the biochemical properties (charge and hydropathy) of the 20 amino acids and the position of the stop signals. The table emphasizes the importance of the central nucleotide in the codons and predicts that purines control the charge while pyrimidines determine the polarity of the amino acids. This prediction was experimentally tested. © 2003 Elsevier Science (USA). All rights reserved.

Open Access: Yes

DOI: 10.1016/S0006-291X(03)00974-4

An open architecture patient monitoring system using standard technologies

Balázs Benyó Zoltán Benyó Péter Várady

Publication Name: IEEE Transactions on Information Technology in Biomedicine

Publication Date: 2002-03-01

Volume: 6

Issue: 1

Page Range: 95-98

Description:

Computer-aided bedside patient monitoring is applied in areas where real-time vital function analysis takes place. Modern bedside monitoring requires not only the networking of bedside monitors with a central monitor but also other standard communication interfaces. In this paper, a novel approach to patient monitoring is introduced. A patient monitoring system was developed and implemented based on an existing industry standard communication network, using standard hardware components and software technologies. The open architecture system design offers scalability, standard interfaces, and flexible signal interpretation possibilities.

Open Access: Yes

DOI: 10.1109/4233.992168