Theoretical Performance Bounds of Model-Based Electrocardiogram Parameter Estimation

10.36227/techrxiv.15176139 ◽

2021 ◽

Author(s):

Reza Sameni ◽

Davood Fattahi

Keyword(s):

Parameter Estimation ◽

Clinical Parameter ◽

Segment Length ◽

Model Parameters ◽

Performance Bounds ◽

Performance Bound ◽

Model Based ◽

Requirements Modeling ◽

R Ratio ◽

Ecg Parameter

<div>Objective: Clinical parameter estimation from the electrocardiogram (ECG) is a recurrent field of research. It is debated that ECG parameter estimation performed by human experts and machines/algorithms is always model-based (implicitly or explicitly). Therefore, depending on the selected data-model, the adopted estimation scheme (least-squares error, maximum likelihood, or Bayesian), and the prior assumptions on the model parameters and noise distributions, any estimation algorithm used in this context has an upper performance bound, which is not exceedable (for the same model and assumptions).</div><div><br></div><div>Method: In this research, we develop a comprehensive theoretical framework for ECG parameter estimation and derive the Cramér-Rao lower bounds (CRLBs) for the most popular signal models used in the ECG modeling literature; namely bases expansions (including polynomials) and sum of Gaussian functions.</div><div><br></div><div>Results: The developed framework is evaluated over real and synthetic data, for three popular applications: T/R ratio estimation, ST-segment analysis and QT-interval estimation, using the state-of-the-art estimators in each context, and compared with the derived theoretical CRLBs.</div><div>Conclusion and Significance: The proposed framework and the derived CRLBs provide fact-based guidelines for the selection of data-models, sampling frequency (beyond the Nyquist requirements), modeling segment length, the number of beats required for average ECG beat extraction, and other factors that influence the accuracy of ECG-based clinical parameter estimation.</div>

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Theoretical Performance Bounds of Model-Based Electrocardiogram Parameter Estimation

10.36227/techrxiv.15176139.v2 ◽

2021 ◽

Author(s):

Davood Fattahi ◽

Reza Sameni

Keyword(s):

Parameter Estimation ◽

Clinical Parameter ◽

Segment Length ◽

Model Parameters ◽

Performance Bounds ◽

Performance Bound ◽

Model Based ◽

Requirements Modeling ◽

R Ratio ◽

Ecg Parameter

<div>Objective: Clinical parameter estimation from the electrocardiogram (ECG) is a recurrent field of research. It is debated that ECG parameter estimation performed by human experts and machines/algorithms is always model-based (implicitly or explicitly). Therefore, depending on the selected data-model, the adopted estimation scheme (least-squares error, maximum likelihood, or Bayesian), and the prior assumptions on the model parameters and noise distributions, any estimation algorithm used in this context has an upper performance bound, which is not exceedable (for the same model and assumptions).</div><div><br></div><div>Method: In this research, we develop a comprehensive theoretical framework for ECG parameter estimation and derive the Cramér-Rao lower bounds (CRLBs) for the most popular signal models used in the ECG modeling literature; namely bases expansions (including polynomials) and sum of Gaussian functions.</div><div><br></div><div>Results: The developed framework is evaluated over real and synthetic data, for three popular applications: T/R ratio estimation, ST-segment analysis and QT-interval estimation, using the state-of-the-art estimators in each context, and compared with the derived theoretical CRLBs.</div><div>Conclusion and Significance: The proposed framework and the derived CRLBs provide fact-based guidelines for the selection of data-models, sampling frequency (beyond the Nyquist requirements), modeling segment length, the number of beats required for average ECG beat extraction, and other factors that influence the accuracy of ECG-based clinical parameter estimation.</div>

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Parameter estimation and performance bounds for radiometric model-based non-contact temperature measurements

2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) ◽

10.1109/i2mtc.2017.7969763 ◽

2017 ◽

Author(s):

Dominik Exel ◽

Bernhard Zagar ◽

Stefan Schuster ◽

Vera Ganglberger ◽

Johann Reisinger

Keyword(s):

Parameter Estimation ◽

Temperature Measurements ◽

Contact Temperature ◽

Performance Bounds ◽

Model Based ◽

And Performance

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Model-Based MR Parameter Mapping With Sparsity Constraints: Parameter Estimation and Performance Bounds

IEEE Transactions on Medical Imaging ◽

10.1109/tmi.2014.2322815 ◽

2014 ◽

Vol 33 (9) ◽

pp. 1832-1844 ◽

Cited By ~ 44

Author(s):

Bo Zhao ◽

Fan Lam ◽

Zhi-Pei Liang

Keyword(s):

Parameter Estimation ◽

Performance Bounds ◽

Parameter Mapping ◽

Model Based ◽

Sparsity Constraints ◽

And Performance

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Model-based Parameter Estimation Method for Terahertz Signals

2020 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD) ◽

10.1109/icsmd50554.2020.9261749 ◽

2020 ◽

Author(s):

Yafei Xu ◽

Liuyang Zhang ◽

Xuefeng Chen ◽

Zhen Zhang ◽

Zhonglei Shen

Keyword(s):

Parameter Estimation ◽

Estimation Method ◽

Model Based ◽

Parameter Estimation Method

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A Model-Based Tool for Assessing the Impact of Land Use Change Scenarios on Flood Risk in Small-Scale River Systems—Part 1: Pre-Processing of Scenario Based Flood Characteristics for the Current State of Land Use

Hydrology ◽

10.3390/hydrology8030102 ◽

2021 ◽

Vol 8 (3) ◽

pp. 102

Author(s):

Frauke Kachholz ◽

Jens Tränckner

Keyword(s):

Land Use ◽

River Flow ◽

Land Use Changes ◽

Small Rivers ◽

Small Scale ◽

Model Parameters ◽

Ungauged Catchments ◽

Model Based ◽

Current State ◽

The Impact

Land use changes influence the water balance and often increase surface runoff. The resulting impacts on river flow, water level, and flood should be identified beforehand in the phase of spatial planning. In two consecutive papers, we develop a model-based decision support system for quantifying the hydrological and stream hydraulic impacts of land use changes. Part 1 presents the semi-automatic set-up of physically based hydrological and hydraulic models on the basis of geodata analysis for the current state. Appropriate hydrological model parameters for ungauged catchments are derived by a transfer from a calibrated model. In the regarded lowland river basins, parameters of surface and groundwater inflow turned out to be particularly important. While the calibration delivers very good to good model results for flow (Evol =2.4%, R = 0.84, NSE = 0.84), the model performance is good to satisfactory (Evol = −9.6%, R = 0.88, NSE = 0.59) in a different river system parametrized with the transfer procedure. After transferring the concept to a larger area with various small rivers, the current state is analyzed by running simulations based on statistical rainfall scenarios. Results include watercourse section-specific capacities and excess volumes in case of flooding. The developed approach can relatively quickly generate physically reliable and spatially high-resolution results. Part 2 builds on the data generated in part 1 and presents the subsequent approach to assess hydrologic/hydrodynamic impacts of potential land use changes.

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Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Entropy ◽

10.3390/e23040387 ◽

2021 ◽

Vol 23 (4) ◽

pp. 387

Author(s):

Yiting Liang ◽

Yuanhua Zhang ◽

Yonggang Li

Keyword(s):

Parameter Estimation ◽

Kinetic Model ◽

Model Parameters ◽

Hydrogen Ions ◽

Removal Process ◽

Cobalt Removal ◽

Estimation Scheme ◽

Zinc Hydrometallurgy ◽

The Impact ◽

Parameter Estimation Scheme

A mechanistic kinetic model of cobalt–hydrogen electrochemical competition for the cobalt removal process in zinc hydrometallurgical was proposed. In addition, to overcome the parameter estimation difficulties arising from the model nonlinearities and the lack of information on the possible value ranges of parameters to be estimated, a constrained guided parameter estimation scheme was derived based on model equations and experimental data. The proposed model and the parameter estimation scheme have two advantages: (i) The model reflected for the first time the mechanism of the electrochemical competition between cobalt and hydrogen ions in the process of cobalt removal in zinc hydrometallurgy; (ii) The proposed constrained parameter estimation scheme did not depend on the information of the possible value ranges of parameters to be estimated; (iii) the constraint conditions provided in that scheme directly linked the experimental phenomenon metrics to the model parameters thereby providing deeper insights into the model parameters for model users. Numerical experiments showed that the proposed constrained parameter estimation algorithm significantly improved the estimation efficiency. Meanwhile, the proposed cobalt–hydrogen electrochemical competition model allowed for accurate simulation of the impact of hydrogen ions on cobalt removal rate as well as simulation of the trend of hydrogen ion concentration, which would be helpful for the actual cobalt removal process in zinc hydrometallurgy.

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Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm

Bulletin of the Polish Academy of Sciences Technical Sciences ◽

10.1515/bpasts-2017-0053 ◽

2017 ◽

Vol 65 (4) ◽

pp. 479-488 ◽

Cited By ~ 4

Author(s):

A. Boboń ◽

A. Nocoń ◽

S. Paszek ◽

P. Pruski

Keyword(s):

Parameter Estimation ◽

Objective Function ◽

Optimization Algorithm ◽

Least Squares Method ◽

Synchronous Generator ◽

Operating Conditions ◽

Model Parameters ◽

State Variables ◽

Starting Point ◽

Gradient Optimization

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

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