Biomedical Signal Analysis: A Case-Study Approach (IEEE Press Series on Biomedical Engineering)

✍ Scribed by Rangaraj M. Rangayyan

• Publisher: Wiley-IEEE Press
• Year: 2001
• Tongue: English
• Leaves: 555
• Edition: 1
• Category: Library

✦ Synopsis

The development of techniques to analyze biomedical signals, such as electro-cardiograms, has dramatically affected countless lives by making possible improved noninvasive diagnosis, online monitoring of critically ill patients, and rehabilitation and sensory aids for the handicapped. Rangaraj Rangayyan supplies a practical, hands-on field guide to this constantly evolving technology in Biomedical Signal Analysis, focusing on the diagnostic challenges that medical professionals continue to face. Dr. Rangayyan applies a problem-solving approach to his study. Each chapter begins with the statement of a different biomedical signal problem, followed by a selection of real-life case studies and the associated signals. Signal processing, modeling, or analysis techniques are then presented, starting with relatively simple "textbook" methods, followed by more sophisticated research approaches. The chapter concludes with one or more application solutions; illustrations of real-life biomedical signals and their derivatives are included throughout.Among the topics addressed are:Concurrent, coupled, and correlated processesFiltering for removal of artifactsEvent detection and characterizationFrequency-domain characterizationModeling biomedical systemsAnalysis of nonstationary signalsPattern classification and diagnostic decisionThe chapters also present a number of laboratory exercises, study questions, and problems to facilitate preparation for class examinations and practical applications. Biomedical Signal Analysis provides a definitive resource for upper-level under-graduate and graduate engineering students, as well as for practicing engineers, computer scientists, information technologists, medical physicists, and data processing specialists.An authoritative assessment of the problems and applications of biomedical signals, rooted in practical case studiesAn Instructor Support FTP site is available from the Wiley editorial department: ftp://ftp.ieee.org/uploads/press/rangayyan

✦ Table of Contents

Front Matter......Page 1
References......Page 0
Table of Contents......Page 3
Dedication......Page 11
Background and Motivation......Page 12
Intended Readership......Page 14
Teaching and Learning Plan......Page 15
About the Author......Page 17
Acknowledgments......Page 19
Symbols and Abbreviations......Page 22
1.1 The Nature of Biomedical Signals......Page 29
1.2.1.1 Resting Potential......Page 33
1.2.1.3 Repolarization......Page 34
1.2.2 The Electroneurogram (ENG)......Page 37
1.2.3 The Electromyogram (EMG)......Page 39
1.2.4 The Electrocardiogram (ECG)......Page 42
1.2.4.1 The Heart......Page 46
1.2.4.2 The Electrical System of the Heart......Page 47
1.2.4.3 ECG Signal Acquisition......Page 50
08112_01b......Page 54
1.2.5 The Electroencephalogram (EEG)......Page 56
1.2.6 Event-Related Potentials (ERPs)......Page 58
1.2.7 The Electrogastrogram (EGG)......Page 59
1.2.8.1 The Genesis of Heart Sounds......Page 62
08112_01c......Page 63
1.2.8.2 Heart Murmurs......Page 65
1.2.9 The Carotid Pulse (CP)......Page 66
1.2.11 The Speech Signal......Page 68
1.2.13.1 The Knee Joint......Page 74
1.2.13.3 Knee-Joint Disorders......Page 75
1.3 Objectives of Biomedical Signal Analysis......Page 76
1.3.2 Active versus Passive Procedures......Page 78
1.3.3 The Human - Instrument System......Page 79
1.4.1 Accessibility of the Variables to Measurement......Page 80
1.4.3 Inter-Relationships and Interactions among Physiological Systems......Page 81
1.4.5 Physiological Artifacts and Interference......Page 82
1.5 Computer-Aided Diagnosis......Page 83
1.6 Remarks......Page 85
1.7 Study Questions and Problems......Page 86
1.8 Laboratory Exercises and Projects......Page 87
2. Analysis of Concurrent, Coupled, and Correlated Processes......Page 88
2.2.1.2 Solution......Page 89
2.2.2 The Phonocardiogram and the Carotid Pulse......Page 90
2.2.3.2 Solution......Page 91
2.2.4 Cardio-Respiratory Interaction......Page 93
2.2.6 The Knee-Joint and Muscle Vibration Signals......Page 94
2.3 Application: Segmentation of the PCG into Systolic and Diastolic Parts......Page 96
2.6 Laboratory Exercises and Projects......Page 98
3.1 Problem Statement......Page 99
3.1.1 Random Noise, Structured Noise, and Physiological Interference......Page 100
3.1.1.2 Random Noise......Page 101
3.1.1.4 Time Averages......Page 104
3.1.1.6 Structured Noise......Page 106
3.1.2 Stationary versus Nonstationary Processes......Page 107
3.2.2 High-Frequency Noise in the ECG......Page 111
3.2.4 Power-Line Interference in ECG Signals......Page 113
3.2.5 Maternal Interference in Fetal ECG......Page 116
3.2.6 Muscle-Contraction Interference in VAG Signals......Page 117
3.3 Time-Domain Filters......Page 119
3.3.1 Synchronized Averaging......Page 120
3.3.1.1 Illustration of Application......Page 121
3.3.2 Moving-Average Filters......Page 125
3.3.2.1 Relationship of Moving-Average Filtering to Integration......Page 130
3.3.2.2 Illustration of Application......Page 132
3.3.3 Derivative-Based Operators to Remove Low-Frequency Artifacts......Page 135
08112_03b......Page 136
3.3.3.1 Illustration of Application......Page 137
3.4 Frequency-Domain Filters......Page 141
3.4.1 Removal of High-Frequency Noise: Butterworth Lowpass Filters......Page 144
3.4.1.1 Butterworth Lowpass Filter Design Example......Page 148
3.4.1.2 Illustration of Application......Page 150
3.4.2 Removal of Low-Frequency Noise: Butterworth Highpass Filters......Page 153
3.4.3 Removal of Periodic Artifacts: Notch and Comb Filters......Page 156
3.4.3.2 Comb Filter Design Example......Page 159
3.4.3.3 Illustration of Application......Page 161
3.5 Optimal Filtering: The Wiener Filter......Page 163
3.5.1 Illustration of Application......Page 170
3.6 Adaptive Filters for Removal of Interference......Page 172
3.6.1 The Adaptive Noise Canceler......Page 173
3.6.2.1 Illustration of Application......Page 176
3.6.3 The Recursive Least-Squares Adaptive Filter......Page 177
3.6.3.1 Illustration of Application......Page 182
3.7 Selecting an Appropriate Filter......Page 184
3.8 Application: Removal of Artifacts in the ECG......Page 188
3.9 Application: Adaptive Cancellation of the Maternal ECG to Obtain the Fetal ECG......Page 191
3.10 Application: Adaptive Cancellation of Muscle-Contraction Interference in Knee Joint Vibration Signals......Page 192
3.12 Study Questions and Problems......Page 197
3.13 Laboratory Exercises and Projects......Page 201
4.1 Problem Statement......Page 203
4.2.1 The P, QRS, and T Waves in the ECG......Page 204
4.2.2 The First and Second Heart Sounds......Page 205
4.2.4 EEG Rhythms, Waves, and Transients......Page 206
4.3 Detection of Events and Waves......Page 208
4.3.1.1 Illustration of Application......Page 209
4.3.1.2 Illustration of Application......Page 212
4.3.2.2 Highpass Filter......Page 213
4.3.2.6 Adaptive Thresholding......Page 214
4.3.2.7 Searchback Procedure......Page 215
4.3.2.8 Illustration of Application......Page 216
4.4 Correlation Analysis of EEG Channels......Page 217
4.4.1 Detection of EEG Rhythms......Page 219
4.4.1.1 Illustration of Application......Page 220
4.5.1 Coherence Analysis of EEG Channels......Page 226
4.5.1.1 Illustration of Application......Page 229
4.6.1 Detection of EEG Spike-and-Wave Complexes......Page 230
4.7 Detection of the P Wave......Page 231
4.8.1 Generalized Linear Filtering......Page 238
4.8.2 Homomorphic Deconvolution......Page 239
4.8.3.1 The Complex Cepstrum......Page 242
4.8.3.2 Effect of Echoes or Repetitions of a Wavelet......Page 244
4.8.3.3 The Power Cepstrum......Page 246
4.8.3.4 Illustration of Application......Page 247
4.9 Application: ECG Rhythm Analysis......Page 248
4.10 Application: Identification of Heart Sounds......Page 251
4.11 Application: Detection of the Aortic Component of the Second Heart Sound......Page 253
4.12 Remarks......Page 257
4.13 Study Questions and Problems......Page 259
4.14 Laboratory Exercises and Projects......Page 260
5.1 Problem Statement......Page 262
5.2.3 Ectopic Beats......Page 263
5.2.5 PCG Intensity Patterns......Page 264
5.4.1 Correlation Coefficient......Page 265
5.4.2 The Minimum-Phase Correspondent and Signal Length......Page 266
5.4.2.2 Minimum-Phase and Maximum-Phase Components......Page 267
5.4.2.3 The Minimum-Phase Correspondent (MPC)......Page 268
5.4.2.5 Illustration of Application......Page 269
5.4.3 ECG Waveform Analysis......Page 273
5.5 Envelope Extraction and Analysis......Page 274
5.5.1 Amplitude Demodulation......Page 276
5.5.2 Synchronized Averaging of PCG Envelopes......Page 277
5.5.3.1 Illustration of Application......Page 280
5.6 Analysis of Activity......Page 281
5.6.2 Zero-Crossing Rate......Page 284
5.6.3.1 Illustration of Application......Page 285
5.6.4 Form Factor......Page 287
5.7 Application: Parameterization of Normal and Ectopic ECG Beats......Page 288
5.8 Application: Analysis of Exercise ECG......Page 290
5.9 Application: Analysis of Respiration......Page 291
5.11 Remarks......Page 294
5.12 Study Questions and Problems......Page 297
5.13 Laboratory Exercises and Projects......Page 299
6. Frequency-Domain Characterizition of Signals and Systems......Page 301
6.1 Problem Statement......Page 302
6.2.1 The Effect of Myocardial Elasticity on Heart Sound Spectra......Page 303
6.2.2 Frequency Analysis of Murmurs to Diagnose Valvular Defects......Page 304
6.3 The Fourier Spectrum......Page 306
6.4 Estimation of the Power Spectral Density Function......Page 311
6.4.1 The Periodogram......Page 312
6.4.2 The Need for Averaging......Page 313
6.4.3 The Use of Windows: Spectral Resolution and Leakage......Page 315
6.4.3.1 Illustration of Application......Page 319
6.4.4 Estimation of the Autocorrelation Function......Page 321
6.4.5 Synchronized Averaging of PCG Spectra......Page 322
6.5 Measures Derived from Power Spectral Density Functions......Page 326
6.5.1 Moments of PSD Functions......Page 329
6.5.2 Spectral Power Ratios......Page 331
6.6 Application: Evaluation of Prosthetic Heart Valves......Page 332
6.7 Remarks......Page 334
6.8 Study Questions and Problems......Page 335
6.9 Laboratory Exercises and Projects......Page 336
7.1 Problem Statement......Page 338
7.2.1 Motor-Unit Firing Patterns......Page 339
7.2.3 Formants and Pitch in Speech......Page 340
7.2.4 Patello-Femoral Crepitus......Page 342
7.3 Point Processes......Page 343
7.4 Parametric System Modeling......Page 350
7.5 Autoregressive or All-Pole Modeling......Page 356
7.5.1 Spectral Matching and Parameterization......Page 362
7.5.2 Optimal Model Order......Page 365
7.5.2.2 Illustration of Application to EEG Signals......Page 366
7.5.3 Relationship between AR and Cepstral Coefficients......Page 369
08112_07b......Page 375
7.6 Pole-Zero Modeling......Page 378
7.6.1.1 Shanks' Method......Page 381
7.6.2.3 The Steiglitz-McBride Method......Page 383
7.6.3.2 Solution......Page 389
7.6.3.3 Illustration of Application to a Synthetic Speech Signal......Page 390
7.6.3.4 Illustration of Application to a Real Speech Signal......Page 393
7.7.1 Sound Generation in Coronary Arteries......Page 394
7.7.2 Sound Generation in Knee Joints......Page 397
7.8 Application: Analysis of Heart-Rate Variability......Page 400
7.9 Application: Spectral Modeling and Analysis of PCG Signals......Page 403
7.11 Remarks......Page 409
7.12 Study Questions and Problems......Page 412
7.13 Laboratory Exercises and Projects......Page 413
8. Analysis of Nonstationary Signals......Page 414
8.2.1 Heart Sounds and Murmurs......Page 415
8.2.3 Articular Cartilage Damage and Knee-Joint Vibrations......Page 416
8.3 Time-Variant Systems......Page 419
8.3.1 Characterization of Nonstationary Signals and Dynamic Systems......Page 420
8.4 Fixed Segmentation......Page 422
8.4.1 The Short-Time Fourier Transform......Page 423
8.4.2 Considerations in Short-Time Analysis......Page 425
8.4.2.1 Illustration of Application......Page 427
8.5 Adaptive Segmentation......Page 428
8.5.1.1 Analysis of Spectral Change......Page 431
8.5.1.2 Algorithm for Adaptive Segmentation......Page 432
8.5.2 ACF Distance......Page 436
8.5.3 The Generalized Likelihood Ratio......Page 437
8.5.4 Comparative Analysis of the ACF, SEM, and GLR Methods......Page 439
08112_08b......Page 440
8.6 Use of Adaptive Filters for Segmentation......Page 442
8.6.1 Monitoring the RLS Filter......Page 443
8.6.2.1 Forward and Backward Prediction......Page 444
8.6.2.2 The Burg-Lattice Method......Page 447
8.6.2.3 RLSL Algorithm for Adaptive Segmentation......Page 450
8.6.2.4 Illustration of Application......Page 453
8.7 Application: Adaptive Segmentation of EEG Signals......Page 454
8.9 Application: Time-Varying Analysis of Heart-Rate Variability......Page 461
8.12 Laboratory Exercises and Projects......Page 467
9. Pattern Classification and Diagnostic Decision......Page 468
9.2.1 Diagnosis of Bundle-Branch Block......Page 469
9.2.2 Normal or Ectopic ECG Beat?......Page 470
9.2.4 Is a Murmur Present?......Page 471
9.3 Pattern Classification......Page 472
9.4.1 Discriminant and Decision Functions......Page 473
9.4.2 Distance Functions......Page 474
9.4.3 The Nearest-Neighbor Rule......Page 475
9.5.1 Cluster-Seeking Methods......Page 476
9.5.1.1 A Simple Cluster-Seeking Algorithm......Page 478
9.5.1.3 The K-Means Algorithm......Page 479
9.6.1 Likelihood Functions and Statistical Decision......Page 480
9.6.2 Bayes Classifier for Normal Patterns......Page 483
9.7 Logistic Regression Analysis......Page 485
9.8.1 The Leave-One-Out Method......Page 486
9.9 Neural Networks......Page 487
9.10 Measures of Diagnostic Accuracy and Cost......Page 489
9.10.1 Receiver Operating Characteristics......Page 492
9.10.2 McNemar's Test of Symmetry......Page 495
9.11 Reliability of Classifiers and Decisions......Page 496
9.12 Application: Normal versus Ectopic ECG Beats......Page 497
9.13 Application: Detection of Knee-Joint Cartilage Pathology......Page 503
9.14 Remarks......Page 506
9.15 Study Questions and Problems......Page 508
9.16 Laboratory Exercises and Projects......Page 510
References......Page 511
B......Page 531
C......Page 532
D......Page 534
E......Page 535
F......Page 539
H......Page 541
K......Page 542
M......Page 543
N......Page 545
P......Page 546
S......Page 550
V......Page 553
W......Page 554
Z......Page 555

✦ Subjects

Медицинские дисциплины;Медицинские приборы и аппараты;