Seamless Healthcare Monitoring (eBook)

Toshiyo Tamura is Professor at Waseda University.Wenxi Chen is Professor at The University of Aizu.

Preface 5
Contents 9
Contributors 11
Abbreviations 14
Part I: Bioelectric Signals 18
1: Electrocardiogram 19
1.1 Introduction 19
1.2 Acquisition 21
1.2.1 Action Potential and Origin of ECG 22
1.2.2 Electrodes and the Electrode-Skin Interface 24
1.2.3 Device Modalities 29
1.2.3.1 Wearable 29
1.2.3.2 Attachable 30
1.2.3.3 Invisible 31
1.3 Analysis 32
1.3.1 Noise Suppression 36
1.3.2 Characterization of ECG Features 37
1.3.3 HRV Analysis 37
1.3.3.1 Preprocessing of RRI Data 37
1.3.3.2 Measures in the Temporal Domain 39
1.3.3.3 Measures in the Frequency Domain 40
1.3.3.4 Measures in the Nonlinear Domain 42
1.3.3.5 Heart Rate Turbulence (HRT) 44
1.4 Application 46
1.4.1 Clinical Diagnosis 46
1.4.2 Daily Healthcare 47
1.5 Summary and Outlook 51
References 54
2: Electroencephalogram 61
2.1 Introduction 61
2.2 Principle 62
2.2.1 Introduction 62
2.2.2 EEG 62
2.2.2.1 Origin of EEG 62
2.2.2.2 Typical Signals 63
2.2.3 Measurement 68
2.2.3.1 Basic Set Up 68
2.2.3.2 Practical Set Up 70
2.2.4 Signal Processing and Data Analysis 71
2.2.4.1 Overview 71
2.2.4.2 Motion Artefact Removal 72
2.2.4.3 Data-Driven Machine Learning 74
2.2.4.4 Performance Assessment 74
2.2.5 Summary 75
2.3 Modality of Measurement 76
2.3.1 Introduction 76
2.3.2 Electrodes 76
2.3.3 Electrode Attachments to the Scalp 80
2.3.4 Instrumentation 82
2.3.4.1 Overview 82
2.3.4.2 Research Lab/Inpatient 82
2.3.4.3 Ambulatory 82
2.3.4.4 Wearable 83
2.3.4.5 Beyond Wearables 84
2.3.5 Summary 86
2.4 Applications 86
2.4.1 Introduction 86
2.4.2 Medical, Clinical and Neuroscience Research Applications 86
2.4.3 Brain-Computer Interfaces (BCIs) 88
2.4.4 Consumer Neuroscience 90
2.4.5 Summary 90
2.5 Conclusions and Future Prospects 91
References 92
3: Electromyogram 98
3.1 EMG 98
3.1.1 Introduction 98
3.1.2 EMG Signal 99
3.1.3 The Electromyogram Measurement 100
3.1.3.1 Electrode 100
3.1.3.2 SEMG Signal Conditioning 102
3.1.3.3 Signal Processing 102
3.1.4 Application 103
3.1.4.1 Lower Back Pain 105
3.1.4.2 Stroke 106
3.1.4.3 Epilepsy 107
3.1.4.4 Parkinson´s Disease (PD) 108
3.1.4.5 Human-Machine Interface (HMI) 109
3.1.4.6 Sports 110
3.1.5 Discussion and Conclusion 112
References 112
Part II: Pressure Signals 116
4: Blood Pressure 117
4.1 Introduction 117
4.2 Indirect Pressure Monitor 120
4.2.1 Auscultatory Sphygmomanometer 120
4.2.2 Oscillometric Method 122
4.2.3 Continuous Blood Pressure Monitor 123
4.2.3.1 Unloaded Method 123
4.2.3.2 Tonometry 124
4.2.4 Central Aortic Blood Pressure Monitor 125
4.2.5 Pulse Arrival Time and Pulse Transit Time 126
4.2.5.1 Estimation of Cuffless Blood Pressure from Pulse Transit Time and Pulse Arrive Time 126
4.2.5.2 Measurement Methods of PTT 129
4.2.6 A Criterion as a Medical Device 130
4.3 Modality of Measurement 130
4.3.1 Cuff-Based Sphygmomanometer 130
4.3.2 Ambulatory Blood Pressure Monitor (ABPM) 133
4.3.3 Cuffless Blood Pressure Monitor 133
4.3.4 Central Blood Pressure Monitor 135
4.4 Application and Future Prospective 135
References 136
5: Ballistocardiography 141
5.1 Introduction 141
5.2 Principles 142
5.3 Instrumentation 143
5.3.1 Suspension Table 144
5.3.2 Directly from the Head 145
5.3.3 Static Charge Sensitive Bed (SCSB) 145
5.3.4 Strain Gauge-Type Sensors 146
5.3.5 Accelerometers 147
5.3.6 Film-Type Sensors 148
5.3.7 Radar 150
5.4 Signal Processing and Data Analysis 151
5.4.1 Peak Detection 151
5.4.2 Heart Rate Variability 153
5.5 Applications 154
5.5.1 Sleep Evaluation 154
5.5.1.1 Sleep Stage Evaluation 155
5.5.1.2 Sleep Parameters 156
5.5.1.3 Monitoring of Infants in Bed 157
5.5.2 Health Monitoring Chair 158
5.5.3 Smart Weighing Scale 159
5.5.4 Wearable and Mobile Application 161
5.5.5 Clinical Application: Diagnosis of Cardiovascular Diseases 163
References 164
Part III: Pulse and Flow 170
6: Photoplethysmogram 171
6.1 Introduction 171
6.2 Photoplethysmography 172
6.2.1 Principles 172
6.2.2 Light Wavelengths 173
6.2.3 Transmitted and Reflected Signals 174
6.2.4 Photoplethysmographic Imaging (PPGi) 174
6.3 Factors Affecting PPG Recording 176
6.3.1 Measurement Site of Probe in General PPG 176
6.3.2 Distance of Photoplethysmographic Imaging 179
6.3.3 Probe Contact Force 180
6.3.4 Signal Processing 182
6.3.4.1 Introduction 182
6.3.4.2 Moving Average Filter 182
6.3.4.3 Fourier Analysis 182
6.3.4.4 Adaptive Filter 183
6.3.4.5 Model-Based Algorithm 188
6.4 Modality of Measurement 189
6.4.1 Wearable Pulse Rate 189
6.4.2 PPG Imaging 190
6.5 Applications 190
6.5.1 Pulse Rate and Pulse Rate Variability 190
6.5.2 Respiratory Rate 190
6.5.3 Peripheral Circulation 191
6.5.4 Blood Pressure 192
6.5.5 Clinical Trials 192
6.5.5.1 Cardiac Index 192
6.5.5.2 Acceleration PPG 192
6.5.5.3 Blood Flow, Peripheral Circulation, and Microcirculation 193
6.5.5.4 Skin 193
6.5.6 Oxygen Saturation 194
6.5.7 Sports and Exercise 194
6.6 Conclusion and Future Perspectives 194
References 195
7: Ultrasound Doppler Velocity and Imaging 205
7.1 Introduction 205
7.2 Principle 206
7.2.1 Definition of Ultrasound 206
7.2.2 Doppler Flowmetry 207
7.2.3 Pulse Doppler Flowmetry 208
7.2.4 Ultrasound Imaging 210
7.2.5 Signal Processing in Ultrasound Imaging 213
7.3 Modality of Measurement 213
7.4 Applications of Handheld Portable Ultrasound Machines 215
7.4.1 Point-of-Care Ultrasound 215
7.4.2 Bladder Volume 215
7.4.3 Bone Therapy with Wearable Ultrasound 217
7.5 Conclusion and Future Prospects 217
References 218
Part IV: Motion and Force 220
8: Wearable Units 221
8.1 Introduction 221
8.2 Principles 221
8.2.1 Principles of Inertial Sensors 221
8.2.1.1 Accelerometers 222
8.2.1.2 Gyroscopic Sensors 224
8.2.2 Magnetic Sensors 227
8.2.3 Angle Measurement 232
8.2.4 Ground Force Sensors and Insole Sensors 232
8.2.5 In-Shoe Force and Pressure Measurement 233
8.2.6 Force Sensor for Sleep Condition and Respiration on the Bed 236
8.3 Modality of Measurement 236
8.3.1 Wearable Inertial Sensors 236
8.3.2 Invisible Sensors 238
8.4 Parameters Obtained from Inertia Sensors 239
8.4.1 Mathematical Analyses 239
8.4.1.1 Comparison Between Rehabilitation Score and Acceleration 241
8.4.2 Applications for Wearable Motion Sensors 242
8.4.2.1 Fall Risk Assessment with Rehabilitation Battery 242
8.4.2.2 Fall Detection 245
8.4.3 Quantitative Evaluation of Hemiplegic Patients 245
8.4.3.1 Clinical Assessment for Parkinson´s Disease 246
8.4.3.2 Energy Expenditure 247
8.4.3.3 Sleep Performance 248
8.4.3.4 Sport Performance 249
8.5 Practical Considerations for Wearable Inertial Sensor Applications in Clinical Practice and Future Research Directions 249
References 249
9: Smart Textile Suit 260
9.1 Introduction 260
9.2 Principle 261
9.2.1 Optical Motion Capture Systems 261
9.2.2 Inertial Motion Capture Systems 262
9.2.3 Textile Systems 264
9.2.3.1 Biomechanical and Electrical Fabric Sensors 264
9.2.3.2 Textile Goniometer 265
9.3 Modality of Measurement 267
9.4 Applications 271
9.4.1 Rehabilitation: Stroke Patients Ambulatory Monitoring 271
9.4.1.1 Data Fusion: Shoulder Movement Detection 276
9.4.2 Multisensorial Platform for Ambient and Assistance Living Applications 279
9.5 Conclusion and Future Prospects 284
References 285
Part V: Temperature 287
10: Body Temperature, Heat Flow, and Evaporation 288
10.1 Introduction 288
10.2 Principle 289
10.2.1 Body Temperature 289
10.2.2 Intermittent and Continuous Temperature Monitoring 290
10.2.3 Principle of Temperature Detection 291
10.2.3.1 Contact Measurement 292
10.2.3.2 Noncontact Thermometer 293
10.2.4 Heat Flow Sensor 295
10.2.5 Evaporation Monitor 296
10.3 Modality of Measurement 297
10.3.1 Wearable Temperature Monitors 297
10.3.1.1 Skin Thermometer 297
10.3.1.2 Wearable Deep Body Thermometers 301
10.3.2 Adhesive Thermometers 302
10.3.2.1 Solid Thermometers with Adhesive Plaster 302
10.3.2.2 Disposable Transfer Tattoo Temperature Monitor 304
10.3.3 Radiation Thermometer: Invisible Sensor 307
10.3.3.1 Infrared and microwave radiation 307
10.3.3.2 Invisible Sensor: Mirror Type 308
10.3.4 Heat Flow 308
10.3.5 Evaporation 309
10.3.5.1 Wearable Sweat Sensor 310
10.3.5.2 Disposable Tattoo Type 310
10.4 Application 311
10.4.1 Fever 311
10.4.2 Circadian Rhythm 311
10.4.3 Energy Expenditure Monitored by Heat Flow 311
10.4.4 Physical Exercise and Stress Monitored by Evaporation Monitor 311
10.5 Conclusion and Future Prospects 312
References 312
Part VI: Gases and Chemical Substances 315
11: Gases 316
11.1 Introduction 316
11.2 Oxygen Measurement 317
11.2.1 Introduction 317
11.2.2 Pulse Oximeter 317
11.2.2.1 Oxygen Saturation of Arterial Blood 318
11.2.2.2 Principle of the Pulse Oximeter 318
11.2.2.3 Pulse Oximeters 322
Electrical Circuit 322
Portable Pulse Oximeters 323
Accuracy 326
Multiwavelength Pulse Oximeter 328
Integration 328
11.2.2.4 Prospects for Wearable Pulse Oximeters 329
11.3 The Capnometer 330
11.3.1 Measuring Methods Using a Capnometer 330
11.3.2 Sidestream and Mainstream Methods 332
11.3.3 The Capnogram 333
11.3.4 Application to Wearable Sensors 336
References 337
12: Chemical Substances 340
12.1 Gas and Odor 340
12.1.1 Introduction 340
12.1.2 Human Odor-Based Sensors 341
12.2 Glucose 343
12.2.1 Introduction 343
12.2.2 Glucose Sensors 344
12.2.3 Noninvasive Glucose Monitoring Devices 346
12.3 Trace Elements and Bacteria from Saliva, Tears, Sweat, Urine, and Excrement 347
12.3.1 Introduction 347
12.3.2 Saliva-Based Sensors 349
12.3.3 Tear-Based Sensors 351
12.3.4 Sweat-Based Sensors 352
12.3.5 Urine- and Excrement-Based Sensors 353
12.3.6 Blood Oxygen-Based Sensors 355
12.4 Biomarker 356
12.4.1 Introduction 356
12.4.2 Protein Biomarker Analysis 356
12.4.3 Nucleic Acid-Based Biomarkers 358
12.4.4 Direct Analysis of Cancer Cells 360
12.5 Conclusion 361
References 362
Part VII: Nutrition and Energy Expenditure 371
13: Automatic Dietary Monitoring Using Wearable Accessories 372
13.1 Introduction 372
13.1.1 Concept of Automatic Dietary Monitoring (ADM) 373
13.1.2 Towards Structuring ADM Methods 374
13.2 Physiological Processes Related to Food Intake 375
13.2.1 Oral Stage 376
13.2.1.1 Process Model of Feeding 379
13.2.1.2 Food Breakdown and Bolus Formation During Mastication 380
13.2.2 Pharyngeal Stage 381
13.2.3 Oesophageal Stage 381
13.2.4 Dietary Activity Modelling 382
13.3 Dietary dimensions 386
13.4 Preparation 387
13.5 Ingestion 388
13.6 Processing 393
13.7 Deglutition 397
13.7.1 Motion from the Skin Surface 398
13.7.2 Sound 399
13.7.3 Muscular Activity 400
13.7.4 Electrical Impedance and Resistance 401
13.7.5 Apnoeas 402
13.8 Digestion 402
13.8.1 Gastric Motility 402
13.8.2 Body Weight 403
13.8.3 Cardiac Responses 404
13.8.4 Diet-Induced Thermogenesis 404
13.8.5 Glucose Concentration 405
13.9 Eating Scene 405
13.10 Conclusion 407
References 408
14: Physical Activity 416
14.1 Introduction 416
14.2 History/State of the Art 417
14.3 Sensors 419
14.3.1 Inertial 419
14.3.2 Biopotential 420
14.3.3 Bioimpedance 422
14.3.4 Optical 423
14.4 Human Kinetics 425
14.4.1 Activity Classification 425
14.4.2 Rest 427
14.4.3 Walking and Running 428
14.4.3.1 Cadence and Step Count 428
14.4.3.2 Speed and Distance 429
14.4.3.3 Running Gait Analysis 430
14.4.4 Swimming 432
14.4.4.1 Stroke Count 432
14.4.4.2 Lap Count 433
14.4.4.3 Swimming Efficiency 433
14.5 Cardiac Activity 434
14.5.1 Heart Rate and Heart Rate Variability 434
14.5.1.1 Time Domain Analysis of HRV 436
Statistical Methods 436
Geometrical Methods 436
14.5.1.2 Frequency Domain Analysis of HRV 437
14.5.1.3 Physiological Interpretation and Application 437
14.6 Energy Expenditure 439
14.6.1 Laboratory Systems 439
14.6.1.1 Activity Diary 439
14.6.1.2 Isotopic Measurements 439
14.6.1.3 Direct Calorimetry 440
14.6.1.4 Indirect Calorimetry 440
14.6.2 Wearable Systems 440
14.6.2.1 Pedometers 440
14.6.2.2 Actigraphs 441
14.6.2.3 Heart Rate-Level Methods 441
14.6.2.4 Hybrid Methods 442
14.6.3 Summary Table 443
14.7 Recovery 443
14.7.1 Post-exercise 443
14.7.2 Sleep 445
14.8 Framework for Validation of Activity Profiling Systems 447
14.8.1 Design of Experimental Protocols 448
14.8.2 Approval of an Experimental Protocol 449
14.8.3 Execution and Monitoring of the Measurement Campaign 449
14.8.4 Statistical Analysis and Reporting 449
14.9 Conclusion 451
References 452
Index 459