| Description |
1 online resource |
| Contents |
Cover -- Half-title -- Title page -- Copyright information -- Dedication -- Contents -- Preface -- 1 Introduction to Measurement Systems -- 1.1 Information Flow -- 1.2 Design of the Book -- 1.3 Notation -- 2 Probability -- 2.1 Introduction -- 2.2 Probability Axioms -- 2.3 Consequences of the Axioms -- 2.4 Conditional Probability -- 2.5 Bayes' Formula -- 2.6 Statistically Independent Events -- 2.7 Problems -- 3 Statistics of Random Processes -- 3.1 Univariate Continuous Random Variables -- 3.2 Discrete Random Variables -- 3.3 Jointly Distributed Random Variables -- 3.4 Data Statistics |
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3.5 Second-Order Statistics: Matrix Forms -- 3.6 Stationary Random Processes -- 3.7 Continuous-Time Covariance and Correlation -- 3.8 Ergodic Processes -- 3.9 Multivariate Normal Density -- 3.10 Mixture Densities -- 3.11 Functions of Random Variables -- 3.12 Regression Analysis -- 3.13 Central Limit Theorem -- 3.14 Information -- 3.15 Problems -- 4 Spatiotemporal Models of the Measurement Process -- 4.1 Introduction -- 4.2 Measurement Equations -- 4.3 Signal Modeling Tools -- 4.4 An Ultrasonic Measurement -- 4.5 1-D Convolution by Matrix Multiplication -- 4.6 2-D Direct Numerical Convolution |
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4.7 2-D Convolution by Matrix Multiplication -- 4.8 Problems -- 5 Basis Decomposition I -- 5.1 Introduction to Principal Components Analysis -- 5.2 Data Spaces -- 5.3 Orthonormal Basis -- 5.4 Fourier Series -- 5.5 Continuous-Time Fourier Transform -- 5.6 Fourier Convolution Theorem -- 5.7 Discrete-Time Fourier Transform -- 5.8 Discrete Fourier Transform -- 5.9 Fourier Analysis of 2-D LTI/LSI Measurement Systems -- 5.10 Even-Odd Real-Imaginary Symmetries -- 5.11 Short-Time Fourier Transform -- 5.12 Power Spectral Density -- 5.13 Passing Random Processes through Linear Systems |
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5.14 Examples from Research -- 5.15 Problems -- 6 Basis Decomposition II -- 6.1 Eigenanalysis with a Fourier Basis -- 6.2 What Do Eigenstates Describe? -- 6.3 Eigenanalysis Connections to DFT -- 6.4 Measurements as Vector-Space Transformations -- 6.5 Singular-Value Decomposition -- 6.6 SVD Indicates Dimensionality of Motion -- 6.7 Linear Shift-Varying Measurement Systems -- 6.8 Compressed Sensing/Compressive Sampling Methods -- 6.9 Analyzing Systems of Chemical Reactions -- 6.10 Problems -- 7 Projection Radiography -- 7.1 Acquisition-Stage Processing: Modeling Photon Detection |
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7.2 Contrast Transfer -- 7.3 Noise Power Spectrum -- 7.4 Spatial Resolution -- 7.5 Relating Quality Measures to Task Performance -- 7.6 Display-Stage Processing -- 7.7 Problems -- 8 Statistical Decision-Making -- 8.1 Experimental Design -- 8.2 Hypothesis Testing -- 8.3 Receiver Operating Characteristic Analysis -- 8.4 Other Performance Metrics -- 8.5 Problems -- 9 Statistical Pattern Recognition with Flow Cytometry Examples -- 9.1 Simulations -- 9.2 Covariance Diagonalization and Whitening Transformations -- 9.3 Discriminant Analysis -- 9.4 Clustering -- 9.5 Problems |
| Summary |
Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineering, computer science, medical physics, and anyone preparing for a career in biomedical sciences and engineering |
| Notes |
Online resource; title from digital title page (viewed on June 02, 2021) |
| Subject |
Biomedical engineering -- Measurement
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Biomedical engineering -- Data processing
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Medical instruments and apparatus.
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Biomedical engineering.
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Biometry.
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Biomedical Engineering
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Biometry
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Equipment and Supplies
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biomedical engineering.
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biometrics.
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Biometry
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Biomedical engineering
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Biomedical engineering -- Data processing
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Medical instruments and apparatus
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| Form |
Electronic book
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| ISBN |
9781316831823 |
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1316831825 |
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