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Biomedical sensors and smart sensinga beginner's guide /
紀錄類型 ： 書目-語言資料,印刷品: 單行本
作者 ： Panja, Ayan.
其他作者 ： Mukherjee, Amartya.
出版者 ： London, UK :Academic Press,2022.
面頁冊數 ： 1 online resource
附註 ： Includes index.
內容註 ： Intro -- Biomedical Sensors and Smart Sensing: A Beginner's Guide -- Copyright -- Contents -- Author's biographies -- Preface -- Acknowledgments -- About the book -- Chapter 1: Introduction -- 1.1. Biomedical sensors and system overview -- 1.2. Physical characteristics -- 1.2.1. Magnetic sensing -- 1.2.2. Electrical sensing -- 1.2.3. Acoustic sensing -- 1.3. System and signal -- 1.3.1. Measurement -- 1.3.2. Biopotentials -- 1.4. Sensor characteristics -- 1.4.1. Sensitivity of the sensor -- 1.4.2. Linearity -- 1.4.3. Sensing errors -- 1.5. Biopotential signal monitoring and biosensors -- 1.6. Conclusion -- References -- Chapter 2: Sensing and data gathering methodology -- 2.1. Signals and noise of sensors -- 2.1.1. Various classes of noise -- 2.1.2. Sensing and measurement -- 2.1.3. Calibration and error scenarios -- 2.2. Flow sensing and measurement technique -- 2.3. Ultrasound-based blood flow sensing -- 2.4. Force-sensing measurement -- 2.5. Foot force measurement using smart shoe -- 2.6. ECG sensing and measurement -- 2.6.1. Electrocardiogram systems -- 2.6.2. Calibration and lead -- 2.6.3. Real-time IoT-based ECG sensing application -- 2.6.4. Heart disease prediction mechanism -- 2.7. EEG fundamentals -- 2.8. EEG signal analysis and classification -- 2.9. Ultrasound sensing for tissues and fetal growth observation -- 2.9.1. Obstetrical sonography -- 2.10. Conclusion -- References -- Chapter 3: Medical signal processing -- 3.1. Overview -- 3.2. Time series analysis -- 3.2.1. Signal overview -- 3.2.2. Some approaches -- 3.2.2.1. Moving average -- 3.2.2.2. Autoregressive moving average -- 3.2.2.3. ARIMA -- 3.3. Multiscale signal processing -- 3.3.1. Various signal processing models -- 3.4. Biomedical imaging and analysis -- 3.4.1. Magnetic resonance imaging -- 3.4.2. Computed tomography -- 3.4.3. Ultrasound-based diagnosis.
內容註 ： 3.4.4. Abdominal imaging for computer-aided diagnosis -- 3.5. Image enhancement -- 3.6. Image classification technique -- 3.7. Wearable and implantable technologies -- 3.8. Conclusion -- References -- Chapter 4: Sensor data analysis -- 4.1. Machine learning preliminaries -- 4.2. Feature engineering -- 4.3. Perceptron learning -- 4.4. Application of machine learning on ECG data -- 4.4.1. ECG raw data classification -- 4.4.2. ECG image classification -- 4.4.3. ECG sound segmentation -- 4.5. Ambient medical data processing -- 4.5.1. Wearable healthcare -- 4.5.2. Wireless body area network -- 4.5.2.1. WBAN implementation for patient monitoring -- 4.6. Conclusion -- References -- Chapter 5: IoT and medical cyberphysical systems road map -- 5.1. Introduction -- 5.2. Ubiquitous sensing paradigm -- 5.2.1. Internet of medical things -- 5.2.2. Smart pill technology -- 5.3. IEEE 1918.1 tactile IoT -- 5.4. Functional architecture -- 5.5. Applications and services -- 5.5.1. Industrial automation -- 5.5.2. Robotics and motion planning -- 5.5.3. Healthcare applications -- 5.5.4. Augmented, virtual, and mixed reality applications -- 5.6. 5G and healthcare -- 5.7. Wi-fi and the femtocell -- 5.8. Software-defined networks -- 5.9. Slicing under SDN -- 5.10. Drone as a component of healthcare and MCPS -- 5.11. UAV-assisted COVID-19 monitoring -- 5.12. The use of sensors and IoT infrastructure to fight against COVID-19 -- 5.12.1. Smart thermometer -- 5.12.2. Networks and cloud robots -- 5.12.3. Autonomous vehicles -- 5.13. Drone delivery in COVID-19 situation -- 5.14. COVID-19 prediction modeling -- 5.15. Conclusion -- References -- Chapter 6: Smart perishable food and medicine management overview -- 6.1. Introduction -- 6.2. Food and medical supply chain perspective -- 6.2.1. Food supply chain -- 6.2.2. Medicine supply chain management.
內容註 ： 6.3. Internet of things concepts -- 6.4. Literature survey -- 6.5. The ecosystem of the IoT-based system -- 6.5.1. IoT solution for medicine -- 6.5.2. Hybrid vehicular DTN-based IoT methodology -- 6.5.3. DTN-based IoT approach -- 6.5.3.1. Direct contact method -- 6.5.3.2. Epidemic routing methods -- 6.5.3.3. Location-based routing mechanism -- 6.6. Analysis of different methodologies -- 6.6.1. Message delivery ratio comparison -- 6.6.2. Buffer usage comparison -- 6.6.3. Comparison of quality of services -- 6.7. Conclusion -- References -- Chapter 7: Overview of data gathering and cloud computing in healthcare -- 7.1. Introduction -- 7.2. Wireless sensor network -- 7.3. Transmission methods -- 7.3.1. Unicast -- 7.3.2. Multicast -- 7.3.3. Broadcast -- 7.3.4. Convergecast -- 7.4. Cloud computing -- 7.5. Medical cloud application -- 7.5.1. Information management and sharing -- 7.5.2. Medical support system -- 7.5.3. Clinical analytics -- 7.6. Issues in healthcare cloud -- 7.7. Conclusion -- References -- Index.
標題 ： Biosensors. -
ISBN ： 9780128230732
ISBN ： 0128230738
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505 0 $aIntro -- Biomedical Sensors and Smart Sensing: A Beginner's Guide -- Copyright -- Contents -- Author's biographies -- Preface -- Acknowledgments -- About the book -- Chapter 1: Introduction -- 1.1. Biomedical sensors and system overview -- 1.2. Physical characteristics -- 1.2.1. Magnetic sensing -- 1.2.2. Electrical sensing -- 1.2.3. Acoustic sensing -- 1.3. System and signal -- 1.3.1. Measurement -- 1.3.2. Biopotentials -- 1.4. Sensor characteristics -- 1.4.1. Sensitivity of the sensor -- 1.4.2. Linearity -- 1.4.3. Sensing errors -- 1.5. Biopotential signal monitoring and biosensors -- 1.6. Conclusion -- References -- Chapter 2: Sensing and data gathering methodology -- 2.1. Signals and noise of sensors -- 2.1.1. Various classes of noise -- 2.1.2. Sensing and measurement -- 2.1.3. Calibration and error scenarios -- 2.2. Flow sensing and measurement technique -- 2.3. Ultrasound-based blood flow sensing -- 2.4. Force-sensing measurement -- 2.5. Foot force measurement using smart shoe -- 2.6. ECG sensing and measurement -- 2.6.1. Electrocardiogram systems -- 2.6.2. Calibration and lead -- 2.6.3. Real-time IoT-based ECG sensing application -- 2.6.4. Heart disease prediction mechanism -- 2.7. EEG fundamentals -- 2.8. EEG signal analysis and classification -- 2.9. Ultrasound sensing for tissues and fetal growth observation -- 2.9.1. Obstetrical sonography -- 2.10. Conclusion -- References -- Chapter 3: Medical signal processing -- 3.1. Overview -- 3.2. Time series analysis -- 3.2.1. Signal overview -- 3.2.2. Some approaches -- 3.2.2.1. Moving average -- 3.2.2.2. Autoregressive moving average -- 3.2.2.3. ARIMA -- 3.3. Multiscale signal processing -- 3.3.1. Various signal processing models -- 3.4. Biomedical imaging and analysis -- 3.4.1. Magnetic resonance imaging -- 3.4.2. Computed tomography -- 3.4.3. Ultrasound-based diagnosis.
505 8 $a3.4.4. Abdominal imaging for computer-aided diagnosis -- 3.5. Image enhancement -- 3.6. Image classification technique -- 3.7. Wearable and implantable technologies -- 3.8. Conclusion -- References -- Chapter 4: Sensor data analysis -- 4.1. Machine learning preliminaries -- 4.2. Feature engineering -- 4.3. Perceptron learning -- 4.4. Application of machine learning on ECG data -- 4.4.1. ECG raw data classification -- 4.4.2. ECG image classification -- 4.4.3. ECG sound segmentation -- 4.5. Ambient medical data processing -- 4.5.1. Wearable healthcare -- 4.5.2. Wireless body area network -- 4.5.2.1. WBAN implementation for patient monitoring -- 4.6. Conclusion -- References -- Chapter 5: IoT and medical cyberphysical systems road map -- 5.1. Introduction -- 5.2. Ubiquitous sensing paradigm -- 5.2.1. Internet of medical things -- 5.2.2. Smart pill technology -- 5.3. IEEE 1918.1 tactile IoT -- 5.4. Functional architecture -- 5.5. Applications and services -- 5.5.1. Industrial automation -- 5.5.2. Robotics and motion planning -- 5.5.3. Healthcare applications -- 5.5.4. Augmented, virtual, and mixed reality applications -- 5.6. 5G and healthcare -- 5.7. Wi-fi and the femtocell -- 5.8. Software-defined networks -- 5.9. Slicing under SDN -- 5.10. Drone as a component of healthcare and MCPS -- 5.11. UAV-assisted COVID-19 monitoring -- 5.12. The use of sensors and IoT infrastructure to fight against COVID-19 -- 5.12.1. Smart thermometer -- 5.12.2. Networks and cloud robots -- 5.12.3. Autonomous vehicles -- 5.13. Drone delivery in COVID-19 situation -- 5.14. COVID-19 prediction modeling -- 5.15. Conclusion -- References -- Chapter 6: Smart perishable food and medicine management overview -- 6.1. Introduction -- 6.2. Food and medical supply chain perspective -- 6.2.1. Food supply chain -- 6.2.2. Medicine supply chain management.
505 8 $a6.3. Internet of things concepts -- 6.4. Literature survey -- 6.5. The ecosystem of the IoT-based system -- 6.5.1. IoT solution for medicine -- 6.5.2. Hybrid vehicular DTN-based IoT methodology -- 6.5.3. DTN-based IoT approach -- 6.5.3.1. Direct contact method -- 6.5.3.2. Epidemic routing methods -- 6.5.3.3. Location-based routing mechanism -- 6.6. Analysis of different methodologies -- 6.6.1. Message delivery ratio comparison -- 6.6.2. Buffer usage comparison -- 6.6.3. Comparison of quality of services -- 6.7. Conclusion -- References -- Chapter 7: Overview of data gathering and cloud computing in healthcare -- 7.1. Introduction -- 7.2. Wireless sensor network -- 7.3. Transmission methods -- 7.3.1. Unicast -- 7.3.2. Multicast -- 7.3.3. Broadcast -- 7.3.4. Convergecast -- 7.4. Cloud computing -- 7.5. Medical cloud application -- 7.5.1. Information management and sharing -- 7.5.2. Medical support system -- 7.5.3. Clinical analytics -- 7.6. Issues in healthcare cloud -- 7.7. Conclusion -- References -- Index.
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Panja, Ayan.
Biomedical sensors and smart sensinga beginner's guide /[electronic resource] :Ayan Kumar Panja, Amartya Mukherjee, Nilanjan Dey. - London, UK :Academic Press,2022. - 1 online resource
Includes index.
Intro -- Biomedical Sensors and Smart Sensing: A Beginner's Guide -- Copyright -- Contents -- Author's biographies -- Preface -- Acknowledgments -- About the book -- Chapter 1: Introduction -- 1.1. Biomedical sensors and system overview -- 1.2. Physical characteristics -- 1.2.1. Magnetic sensing -- 1.2.2. Electrical sensing -- 1.2.3. Acoustic sensing -- 1.3. System and signal -- 1.3.1. Measurement -- 1.3.2. Biopotentials -- 1.4. Sensor characteristics -- 1.4.1. Sensitivity of the sensor -- 1.4.2. Linearity -- 1.4.3. Sensing errors -- 1.5. Biopotential signal monitoring and biosensors -- 1.6. Conclusion -- References -- Chapter 2: Sensing and data gathering methodology -- 2.1. Signals and noise of sensors -- 2.1.1. Various classes of noise -- 2.1.2. Sensing and measurement -- 2.1.3. Calibration and error scenarios -- 2.2. Flow sensing and measurement technique -- 2.3. Ultrasound-based blood flow sensing -- 2.4. Force-sensing measurement -- 2.5. Foot force measurement using smart shoe -- 2.6. ECG sensing and measurement -- 2.6.1. Electrocardiogram systems -- 2.6.2. Calibration and lead -- 2.6.3. Real-time IoT-based ECG sensing application -- 2.6.4. Heart disease prediction mechanism -- 2.7. EEG fundamentals -- 2.8. EEG signal analysis and classification -- 2.9. Ultrasound sensing for tissues and fetal growth observation -- 2.9.1. Obstetrical sonography -- 2.10. Conclusion -- References -- Chapter 3: Medical signal processing -- 3.1. Overview -- 3.2. Time series analysis -- 3.2.1. Signal overview -- 3.2.2. Some approaches -- 3.2.2.1. Moving average -- 3.2.2.2. Autoregressive moving average -- 3.2.2.3. ARIMA -- 3.3. Multiscale signal processing -- 3.3.1. Various signal processing models -- 3.4. Biomedical imaging and analysis -- 3.4.1. Magnetic resonance imaging -- 3.4.2. Computed tomography -- 3.4.3. Ultrasound-based diagnosis.
Electronic reproduction.
Ipswich, MA
Available via World Wide Web.
ISBN: 9780128230732Subjects--Topical Terms:
88426
Biosensors.
LC Class. No.: R857.B54 / P35 2022
Dewey Class. No.: 610.28
Biomedical sensors and smart sensinga beginner's guide /[electronic resource] :Ayan Kumar Panja, Amartya Mukherjee, Nilanjan Dey. - London, UK :Academic Press,2022. - 1 online resource
Includes index.
Intro -- Biomedical Sensors and Smart Sensing: A Beginner's Guide -- Copyright -- Contents -- Author's biographies -- Preface -- Acknowledgments -- About the book -- Chapter 1: Introduction -- 1.1. Biomedical sensors and system overview -- 1.2. Physical characteristics -- 1.2.1. Magnetic sensing -- 1.2.2. Electrical sensing -- 1.2.3. Acoustic sensing -- 1.3. System and signal -- 1.3.1. Measurement -- 1.3.2. Biopotentials -- 1.4. Sensor characteristics -- 1.4.1. Sensitivity of the sensor -- 1.4.2. Linearity -- 1.4.3. Sensing errors -- 1.5. Biopotential signal monitoring and biosensors -- 1.6. Conclusion -- References -- Chapter 2: Sensing and data gathering methodology -- 2.1. Signals and noise of sensors -- 2.1.1. Various classes of noise -- 2.1.2. Sensing and measurement -- 2.1.3. Calibration and error scenarios -- 2.2. Flow sensing and measurement technique -- 2.3. Ultrasound-based blood flow sensing -- 2.4. Force-sensing measurement -- 2.5. Foot force measurement using smart shoe -- 2.6. ECG sensing and measurement -- 2.6.1. Electrocardiogram systems -- 2.6.2. Calibration and lead -- 2.6.3. Real-time IoT-based ECG sensing application -- 2.6.4. Heart disease prediction mechanism -- 2.7. EEG fundamentals -- 2.8. EEG signal analysis and classification -- 2.9. Ultrasound sensing for tissues and fetal growth observation -- 2.9.1. Obstetrical sonography -- 2.10. Conclusion -- References -- Chapter 3: Medical signal processing -- 3.1. Overview -- 3.2. Time series analysis -- 3.2.1. Signal overview -- 3.2.2. Some approaches -- 3.2.2.1. Moving average -- 3.2.2.2. Autoregressive moving average -- 3.2.2.3. ARIMA -- 3.3. Multiscale signal processing -- 3.3.1. Various signal processing models -- 3.4. Biomedical imaging and analysis -- 3.4.1. Magnetic resonance imaging -- 3.4.2. Computed tomography -- 3.4.3. Ultrasound-based diagnosis.
Electronic reproduction.
Ipswich, MA
Available via World Wide Web.
ISBN: 9780128230732Subjects--Topical Terms:
88426
Biosensors.
LC Class. No.: R857.B54 / P35 2022
Dewey Class. No.: 610.28
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