Body Sensor Networking, Design and Algorithms. Saeid Sanei

      

      Table of Contents

      1  Cover

      2  Preface

      3  About the Companion Website

      4  1 Introduction 1.1 History of Wearable Technology 1.2 Introduction to BSN Technology 1.3 BSN Architecture 1.4 Layout of the Book References

      5  2 Physical, Physiological, Biological, and Behavioural States of the Human Body 2.1 Introduction 2.2 Physical State of the Human Body 2.3 Physiological State of Human Body 2.4 Biological State of Human Body 2.5 Psychological and Behavioural State of the Human Body 2.6 Summary and Conclusions References

      6  3 Physical, Physiological, and Biological Measurements 3.1 Introduction 3.2 Wearable Technology for Gait Monitoring 3.3 Physiological Sensors 3.4 Biological Sensors 3.5 Conclusions References

      7  4 Ambulatory and Popular Sensor Measurements 4.1 Introduction 4.2 Heart Rate 4.3 Respiration 4.4 Blood Oxygen Saturation Level 4.5 Blood Pressure 4.6 Blood Glucose 4.7 Body Temperature 4.8 Commercial Sensors 4.9 Conclusions References

      8  5 Polysomnography and Sleep Analysis 5.1 Introduction 5.2 Polysomnography 5.3 Sleep Stage Classification 5.4 Monitoring Movements and Body Position During Sleep 5.5 Conclusions References

      9  6 Noninvasive, Intrusive, and Nonintrusive Measurements 6.1 Introduction 6.2 Noninvasive Monitoring 6.3 Contactless Monitoring 6.4 Implantable Sensor Systems 6.5 Conclusions References

      10  7 Single and Multiple Sensor Networking for Gait Analysis 7.1 Introduction 7.2 Gait Events and Parameters 7.3 Standard Gait Measurement Systems 7.4 Wearable Sensors for Gait Analysis 7.5 Gait Analysis Algorithms Based on Accelerometer/Gyroscope 7.6 Conclusions References

      11  8 Popular Health Monitoring Systems 8.1 Introduction 8.2 Technology for Data Acquisition 8.3 Physiological Health Monitoring Technologies 8.4 Conclusions References

      12  9 Machine Learning for Sensor Networks 9.1 Introduction 9.2 Clustering Approaches 9.3 Classification Algorithms 9.4 Common Spatial Patterns 9.5 Applications of Machine Learning in BSNs and WSNs 9.6 Conclusions References

      13  10 Signal Processing for Sensor Networks 10.1 Introduction 10.2 Signal Processing Problems for Sensor Networks 10.3 Fundamental Concepts in Signal Processing 10.4 Mathematical Data Models 10.5 Transform Domain Signal Analysis 10.6 Time-frequency Domain Transforms 10.7