Bioelectrical signal processing in cardiac and neurological applications:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam [u.a.]
Elsevier Acad. Press
c2005
|
| Schriftenreihe: | Academic Press series in biomedical engineering
|
| Schlagworte: | |
| Online-Zugang: | Publisher description Table of contents only lizenzfrei Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XIII, 668 S. Ill., graph. Darst. 24 cm |
| ISBN: | 0124375529 9780124375529 |
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| 650 | 4 | |a Brain |x Electric properties | |
| 650 | 4 | |a Muscles |x Electric properties | |
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| 650 | 4 | |a Electroencephalography | |
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Datensatz im Suchindex
| _version_ | 1804138822873645056 |
|---|---|
| adam_text | Contents
Preface vii
Chapter 1. Introduction 1
1.1 Biomedical Signal Processing: Objectives and Contexts ... 2
1.1.1 Objectives 2
1.1.2 Contexts 4
1.2 Basics of Bioelectrical Signals 6
1.2.1 On the Cellular Level 6
1.2.2 On the Body Surface 9
1.2.3 Bioelectrical Signals 11
1.3 Signal Acquisition and Analysis 14
1.4 Performance Evaluation 16
1.4.1 Databases 17
1.4.2 Simulation 21
Bibliography 22
Chapter 2. The Electroencephalogram—A Brief Background 25
2.1 The Nervous System 27
2.1.1 Neurons 28
2.1.2 The Cerebral Cortex 30
2.2 The EEG—Electrical Activity Measured on the Scalp .... 31
2.2.1 EEG Rhythms and Waveforms 33
2.2.2 Categorization of EEG Activity 36
2.3 Recording Techniques 37
2.4 EEG Applications 39
2.4.1 Epilepsy 40
2.4.2 Sleep Disorders 44
2.4.3 Brain-Computer Interface 47
Bibliography 50
jj Contents
Chapter 3. EEG Signal Processing 55
3.1 Modeling the EEG Signal 55
3.1.1 Deterministic and Stochastic Signal Properties .... 55
3.1.2 Stochastic Properties 56
3.1.3 Linear, Stochastic Models 63
3.1.4 Nonlinear Modeling of the EEG 67
3.2 Artifacts in the EEG 71
3.2.1 Artifact Characteristics 73
3.2.2 Artifact Processing 76
3.2.3 Artifact Reduction Using Linear Filtering 77
3.2.4 Artifact Cancellation Using Linearly Combined
Reference Signals 78
3.2.5 Adaptive Artifact Cancellation Using Linearly
Combined Reference Signals 83
3.2.6 Artifact Cancellation Using Filtered Reference Signals 87
3.3 Nonparametric Spectral Analysis 91
3.3.1 Fourier-based Power Spectrum Analysis 92
3.3.2 Spectral Parameters 97
3.4 Model-based Spectral Analysis 103
3.4.1 The Autocorrelation/Covariance Methods 106
3.4.2 The Modified Covariance Method 110
3.4.3 Burg s Method 112
3.4.4 Performance and Design Parameters 116
3.4.5 Spectral Parameters 119
3.5 EEG Segmentation 125
3.5.1 Spectral Error Measure—The Periodogram Approach 128
3.5.2 Spectral Error Measure—The Whitening Approach . . 131
3.5.3 Segmentation Performance and Beyond 134
3.6 Joint Time-Frequency Analysis 135
3.6.1 The Short-Time Fourier Transform 137
3.6.2 The Ambiguity Function 142
3.6.3 The Wigner-Ville Distribution 147
3.6.4 General Time-Frequency Distributions—Cohen s Class 153
3.6.5 Model-based Analysis of Slowly Varying Signals .... 158
Bibliography 162
Problems 175
Chapter 4. Evoked Potentials 181
4.1 Evoked Potential Modalities 183
4.1.1 Auditory Evoked Potentials 185
4.1.2 Somatosensory Evoked Potentials 187
4.1.3 Visual Evoked Potentials 188
Contents iii
4.1.4 Evoked Potentials and Cognition 189
4.2 Noise Characteristics 190
4.3 Noise Reduction by Ensemble Averaging 192
4.3.1 Averaging of Homogeneous Ensembles 193
4.3.2 Ensemble Averaging Interpreted as Linear Filtering . 200
4.3.3 Exponential Averaging 202
4.3.4 Averaging of Inhomogeneous Ensembles 207
4.3.5 Spike Artifacts and Robust Averaging 219
4.3.6 The Effect of Latency Shifts 225
4.3.7 Estimation of Latency Shifts 229
4.3.8 Weighting of Averaged Evoked Potentials Using
Ensemble Correlation 236
4.4 Noise Reduction by Linear Filtering 241
4.4.1 Time-Invariant, A Posteriori Filtering 243
4.4.2 Limitations with Time-Invariant, A Posteriori
Filtering 252
4.5 Single-Trial Analysis Using Basis Functions 253
4.5.1 Orthogonal Expansions 254
4.5.2 Sets of Basis Functions 260
4.5.3 Karhunen-Loeve Expansion—Optimal Basis Functions 264
4.5.4 Interpretation as Linear, Time-Variant Filtering . . . 271
4.5.5 Modeling with Damped Sinusoids 272
4.6 Adaptive Analysis Using Basis Functions 278
4.6.1 The Instantaneous LMS Algorithm 279
4.6.2 The Block LMS Algorithm 285
4.7 Wavelets 286
4.7.1 The Wavelet Transform 288
4.7.2 Multiresolution Signal Analysis 292
4.7.3 Multiresolution Signal Analysis—A Classical Example 297
4.7.4 Implementation of the Discrete Wavelet Transform
Using Filter Banks 300
4.7.5 Wavelet Examples 306
4.7.6 Denoising 312
Bibliography 318
Problems 329
Chapter 5. The Electromyogram 337
5.1 The Electrical Activity of Muscles 338
5.1.1 Action Potentials and Motor Units 338
5.1.2 Recording of Myoelectric Signals 343
5.1.3 EMG Applications 345
5.2 Amplitude Estimation in the Surface EMG 347
5.2.1 Signal Model and ML Estimation 347
5.2.2 Modifications of the ML Amplitude Estimator .... 352
5.2.3 Multiple Electrode Sites 356
5.3 Spectral Analysis of the Surface EMG 361
5.4 Conduction Velocity Estimation 365
5.4.1 Two-Channel Time Delay Estimation 367
5.4.2 Multichannel Time Delay Estimation 369
5.5 Modeling the Intramuscular EMG 371
5.5.1 A Signal Model of the MUAP Train 372
5.5.2 MUAP Train Amplitude 377
5.5.3 MUAP Train Power Spectrum 378
5.6 Intramuscular EMG Signal Decomposition 383
5.6.1 MUAP Feature Extraction and Clustering 387
5.6.2 Resolution of Superimposed MUAP Waveforms .... 391
Bibliography 398
Problems 406
Chapter 6. The Electrocardiogram—A Brief Background 411
6.1 Electrical Activity of the Heart 412
6.2 Generation and Recording of an ECG 415
6.2.1 Depolarization and Repolarization 415
6.2.2 ECG Recording Techniques 419
6.2.3 ECG Waves and Time Intervals 426
6.3 Heart Rhythms 430
6.3.1 Sinus Rhythm 431
6.3.2 Premature Beats 433
6.3.3 Atrial Arrhythmias 434
6.3.4 Ventricular Arrhythmias 436
6.3.5 Conduction Blocks 438
6.4 Heartbeat Morphologies 438
6.4.1 Myocardial Ischemia 438
6.4.2 Myocardial Infarction 439
6.5 Noise and Artifacts 440
6.6 Clinical Applications 443
6.6.1 Resting ECG 443
6.6.2 Intensive Care Monitoring 444
6.6.3 Ambulatory Monitoring 444
6.6.4 Stress Test 445
6.6.5 High-Resolution ECG 447
Bibliography 449
Chapter 7. ECG Signal Processing 453
7.1 Baseline Wander 457
7.1.1 Linear, Time-Invariant Filtering 458
7.1.2 Linear, Time-Variant Filtering 467
7.1.3 Polynomial Fitting 470
7.2 Powerline Interference (50/60 Hz) 473
7.2.1 Linear Filtering 473
7.2.2 Nonlinear Filtering 476
7.2.3 Estimation-Subtraction 479
7.3 Muscle Noise Filtering 484
7.4 QRS Detection 485
7.4.1 Signal and Noise Problems 487
7.4.2 QRS Detection as an Estimation Problem 488
7.4.3 Detector Preprocessing 497
7.4.4 Decision Rules 504
7.4.5 Performance Evaluation 507
7.5 Wave Delineation 510
7.6 Data Compression 514
7.6.1 Lossless Compression 517
7.6.2 Lossy Compression—Direct Methods 519
7.6.3 Lossy Compression—Transform-based Methods .... 526
7.6.4 Interbeat Redundancy 533
7.6.5 Interlead Redundancy 536
7.6.6 Quantization and Coding 539
7.6.7 Performance Evaluation 541
Bibliography 545
Problems 557
Chapter 8. ECG Signal Processing: Heart Rate Variability 567
8.1 Acquisition and RR Interval Conditioning 568
8.2 Time Domain Measures 570
8.3 Heart Rhythm Representations 573
8.3.1 The Integral Pulse Frequency Modulation Model . . . 574
8.3.2 Interval Series Representions 578
8.3.3 Event Series Representation 582
8.3.4 Heart Timing Representation 585
8.4 Spectral Analysis of Heart Rate Variability 589
8.4.1 Direct Estimation from Unevenly Spaced Samples . . 592
8.4.2 The Spectrum of Counts 593
8.4.3 Lomb s Periodogram 597
8.5 Clustering of Beat Morphologies 603
8.6 Dealing with Ectopic Beats G05
8.6.1 Correlation-based Correction 608
8.6.2 Interpolation-based Correction 609
8.6.3 The Heart Timing Signal and Ectopic Beats 611
8.7 Interaction with Other Physiological Signals 614
Bibliography 621
Problems 628
Appendix A. Review of Important Concepts 633
A.I Matrix Fundamentals 633
A.I.I Definitions 633
A.1.2 Matrix Decomposition 638
A.1.3 Matrix Optimization 640
A.1.4 Linear Equations 641
A.2 Discrete-Time Stochastic Processes 642
A.2.1 Definitions 642
A.2.2 Stationarity 644
A.2.3 Ergodicity 645
A.2.4 Bias and Consistency 645
A.2.5 Power Spectrum 646
A.2.6 White Noise 646
A.2.7 Filtering of Stochastic Processes 647
Bibliography 648
Appendix B. Symbols and Abbreviations 649
B.I Mathematical Symbols 649
B.2 Abbreviations 658
Index 661
|
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| illustrated | Illustrated |
| indexdate | 2024-07-09T21:34:18Z |
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| isbn | 0124375529 9780124375529 |
| language | English |
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| spelling | Sörnmo, Leif Verfasser aut Bioelectrical signal processing in cardiac and neurological applications Leif Sörnmo ; Pablo Laguna Amsterdam [u.a.] Elsevier Acad. Press c2005 XIII, 668 S. Ill., graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Academic Press series in biomedical engineering Includes bibliographical references and index Brain Electric properties Muscles Electric properties Heart Electric properties Electroencephalography Electromyography Electrocardiography Elektrokardiogramm (DE-588)4070750-7 gnd rswk-swf Biosignalverarbeitung (DE-588)4006899-7 gnd rswk-swf Elektromyographie (DE-588)4014316-8 gnd rswk-swf Elektroencephalogramm (DE-588)4070747-7 gnd rswk-swf Biosignalverarbeitung (DE-588)4006899-7 s Elektroencephalogramm (DE-588)4070747-7 s DE-604 Elektromyographie (DE-588)4014316-8 s Elektrokardiogramm (DE-588)4070750-7 s Laguna, Pablo Sonstige oth http://www.loc.gov/catdir/enhancements/fy0627/2005299724-d.html Publisher description http://www.loc.gov/catdir/enhancements/fy0627/2005299724-t.html Table of contents only http://www.gbv.de/dms/ilmenau/toc/499881834soern.PDF lizenzfrei Inhaltsverzeichnis HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017317793&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Sörnmo, Leif Bioelectrical signal processing in cardiac and neurological applications Brain Electric properties Muscles Electric properties Heart Electric properties Electroencephalography Electromyography Electrocardiography Elektrokardiogramm (DE-588)4070750-7 gnd Biosignalverarbeitung (DE-588)4006899-7 gnd Elektromyographie (DE-588)4014316-8 gnd Elektroencephalogramm (DE-588)4070747-7 gnd |
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| title | Bioelectrical signal processing in cardiac and neurological applications |
| title_auth | Bioelectrical signal processing in cardiac and neurological applications |
| title_exact_search | Bioelectrical signal processing in cardiac and neurological applications |
| title_full | Bioelectrical signal processing in cardiac and neurological applications Leif Sörnmo ; Pablo Laguna |
| title_fullStr | Bioelectrical signal processing in cardiac and neurological applications Leif Sörnmo ; Pablo Laguna |
| title_full_unstemmed | Bioelectrical signal processing in cardiac and neurological applications Leif Sörnmo ; Pablo Laguna |
| title_short | Bioelectrical signal processing in cardiac and neurological applications |
| title_sort | bioelectrical signal processing in cardiac and neurological applications |
| topic | Brain Electric properties Muscles Electric properties Heart Electric properties Electroencephalography Electromyography Electrocardiography Elektrokardiogramm (DE-588)4070750-7 gnd Biosignalverarbeitung (DE-588)4006899-7 gnd Elektromyographie (DE-588)4014316-8 gnd Elektroencephalogramm (DE-588)4070747-7 gnd |
| topic_facet | Brain Electric properties Muscles Electric properties Heart Electric properties Electroencephalography Electromyography Electrocardiography Elektrokardiogramm Biosignalverarbeitung Elektromyographie Elektroencephalogramm |
| url | http://www.loc.gov/catdir/enhancements/fy0627/2005299724-d.html http://www.loc.gov/catdir/enhancements/fy0627/2005299724-t.html http://www.gbv.de/dms/ilmenau/toc/499881834soern.PDF http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017317793&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT sornmoleif bioelectricalsignalprocessingincardiacandneurologicalapplications AT lagunapablo bioelectricalsignalprocessingincardiacandneurologicalapplications |