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Informationen zum Autor Saeid Sanei is a Professor of Biomedical Signal Processing and Machine Learning at Nottingham Trent University and a Visiting Professor to Imperial College London, in the United Kingdom. His major contributions in advanced signal processing techniques such as tensor factorization, cooperative networking, compressive sensing, statistical signal processing, and subspace analysis have applications in physiological signal processing and sensor networks as explored in his three published monograms and over 400 publications. Delaram Jarchi is currently a Lecturer at Essex University. She has been working intensively on sensor networks design and algorithms levels. Her research is focused on designing new algorithms and validation of commercial wearable sensors for robust estimation of physiological parameters such as heart rate, respiratory rate and blood oxygen saturation levels in very unobtrusive ways. She is a senior member of IEEE since 2018. Anthony G. Constantinides is a Professor at Imperial College of London UK. He is an IEEE acknowledged pioneer in signal processing with research interests that span a wide range of applications of the area. Amongst these and relevant to the present book are included topics such as data analytics, acquisition, sensing, transmission, and compression. Inhaltsverzeichnis Preface xiii About the Companion Website xv 1 Introduction 1 1.1 History of Wearable Technology 1 1.2 Introduction to BSN Technology 2 1.3 BSN Architecture 7 1.4 Layout of the Book 10 References 11 2 Physical, Physiological, Biological, and Behavioural States of the Human Body 17 2.1 Introduction 17 2.2 Physical State of the Human Body 17 2.3 Physiological State of Human Body 19 2.4 Biological State of Human Body 23 2.5 Psychological and Behavioural State of the Human Body 24 2.6 Summary and Conclusions 30 References 31 3 Physical, Physiological, and Biological Measurements 35 3.1 Introduction 35 3.2 Wearable Technology for Gait Monitoring 35 3.2.1 Accelerometer and Its Application to Gait Monitoring 36 3.2.1.1 How Accelerometers Operate 37 3.2.1.2 Accelerometers in Practice 39 3.2.2 Gyroscope and IMU 40 3.2.3 Force Plates 41 3.2.4 Goniometer 41 3.2.5 Electromyography 41 3.2.6 Sensing Fabric 42 3.3 Physiological Sensors 42 3.3.1 Multichannel Measurement of the Nerves Electric Potentials 42 3.3.2 Other Sensors 45 3.4 Biological Sensors 48 3.4.1 The Structures of Biological Sensors - The Principles 48 3.4.2 Emerging Biosensor Technologies 51 3.5 Conclusions 51 References 53 4 Ambulatory and Popular Sensor Measurements 59 4.1 Introduction 59 4.2 Heart Rate 59 4.2.1 HR During Physical Exercise 60 4.3 Respiration 62 4.4 Blood Oxygen Saturation Level 67 4.5 Blood Pressure 70 4.5.1 Cuffless Blood Pressure Measurement 71 4.6 Blood Glucose 72 4.7 Body Temperature 73 4.8 Commercial Sensors 74 4.9 Conclusions 75 References 76 5 Polysomnography and Sleep Analysis 83 5.1 Introduction 83 5.2 Polysomnography 84 5.3 Sleep Stage Classification 85 5.3.1 Sleep Stages 85 5.3.2 EEG-Based Classification of Sleep Stages 86 5.3.2.1 Time Domain Features 86 5.3.2.2 Frequency Domain Features 87 5.3.2.3 Time-frequency Domain Features 87 5.3.2.4 Short-time Fourier Transform 88 5.3.2.5 Wavelet Transform 88 5.3.2.6 Matching Pursuit 88 5.3.2.7 Empirical Mode Decomposition 89 5.3.2.8 Nonlinear Features 89 5.3.3 Classification Techniques 90 5.3.3.1 Using Neural Networks 90
