Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing (eBook, ePUB)
Redaktion: Al-Jumaily, Adel; Turchetti, Claudio; Mansour, Ali; Crippa, Paolo
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Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing (eBook, ePUB)
Redaktion: Al-Jumaily, Adel; Turchetti, Claudio; Mansour, Ali; Crippa, Paolo
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The book contains up-to-date noninvasive monitoring and diagnosing systems closely developed by a set of scientists, engineers, and physicians. The chapters are the results of different biomedical projects and theoretical studies that were coupled by simulations and real-world data.
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The book contains up-to-date noninvasive monitoring and diagnosing systems closely developed by a set of scientists, engineers, and physicians. The chapters are the results of different biomedical projects and theoretical studies that were coupled by simulations and real-world data.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 474
- Erscheinungstermin: 29. Februar 2024
- Englisch
- ISBN-13: 9781003838128
- Artikelnr.: 69742165
- Verlag: Taylor & Francis
- Seitenzahl: 474
- Erscheinungstermin: 29. Februar 2024
- Englisch
- ISBN-13: 9781003838128
- Artikelnr.: 69742165
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Adel Al-Jumaily is a researcher and academic leader with more than two decades of experience. He is a Professor at the University of Technology Brunei and a professor research fellow at ENSTA-Bretagne. His research area is Computational Intelligence and Humanized Computational Intelligence. He has published more than 250 peer-reviewed papers. He has 13 patents, 12 of which are sponsored by industry. Adel has supervised more than 40 PhD and master's students and received two supervision awards. Paolo Crippa is an Associate Professor of electronics at the Department of Information Engineering of the Universita Politecnica delle Marche, Ancona, Italy. His research interests include micro and nanoelectronics, statistical device modeling, mixed-signal and RF integrated circuit design, biomedical circuits, systems and signal processing, neural networks, and non-linear system identification. He has published more than 120 papers in international journals, edited books, and conference proceedings. He is a member of the editorial boards and technical program committees of several international scientific journals and conferences. He is an IEEE senior member and a member of the Italian AEIT. Ali Mansour has held many positions: Postdoctoral at LTIRF-INPG (Grenoble- France), Researcher at BMC-RIKEN (Nagoya-Japan), Teacher-Researcher at ENSIETA (Brest-France), Senior-Lecturer at Curtin-University (Perth-Australia), Invited- Professor at ULCO (Calais-France), Professor at Tabuk University (KSA), and recently Professor at ENSTA-Bretagne (Brest-France). He has published numerous refereed publications, several books, and book chapters, and has supervised many Post- Docs, PhDs, and MScs. He is interested in statistics, signal processing, robotics, telecom, biomedical engineering, electronic warfare, and cognitive radio. Claudio Turchetti received the Laurea degree in electronics engineering from the University of Ancona, Italy, in 1979. He joined the Universita Politecnica delle Marche, Ancona, in 1980, where he is currently a Full Professor of Embedded Systems design. He has published more than 160 papers, the most relevant are in IEEE Journal of Solid-State Circuits, IEEE Transactions on Electron Devices, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transaction on Signal Processing, IEEE Transaction on Cybernetics, IEEE Journal of Biomedical and Health Informatics, IEEE Transaction on Consumer Electronics, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, IEEE Access, and IEEE Open Journal on Circuits and Systems.
1. Upper Limb Recovery Prediction Based on Multilevel Mixed Effect EMG
Synergy and Biomarker Values. 2. EMG Feature Extraction Based on
Cardinality with Deep Learning Concepts. 3. Surface Electromyography
Sensors for Human Activity Recognition: Recent Advancements and
Perspectives. 4. ECG signal monitoring and processing in the operating
room. 5. Photoplethysmography and Inertial Sensors in Wearable Devices for
Healthcare: Multimodal Signal Processing for Increasing Accuracy. 6.
Non-invasive system for measuring parameters relevant to sleep quality and
detecting sleep diseases: The data model. 7. PREDICTING INCIDENCE OF STROKE
VIA SUPERVISED MACHINE LEARNING METHODS ON CLASS IMBALANCED DATA. 8.
Ultrasound vector flow imaging, a promising technique towards a new carotid
atheroma risk stratification. 9. A Pre-screening Technique for Coronary
Artery Disease with Multi-channel Phonocardiography and
Electrocardiography. 10. Exploring the feasibility of estimating the
carotid-to-femoral pulse wave velocity using machine learning algorithms.
11. DVT Diagnosis based on HOS & Scattering Operators. 12. Non-invasive
AI-assisted Techniques for 3D Printing of the Heart via Image Analysis:
Current State, Challenges, and Future Directions. 13. COVID-19 and
Pneumonia Detection System using Deep Learning with Chest X-ray Images. 14.
Scattering Operators and high order statistics along with Elastography to
Identify & Characterize Salivary Gland Abnormalities. 15. SA-SVM
Classification-Based Smart Feature Selection Algorithm for Skin Cancer
Detection. 16. A Review on Advanced CNN Architecture in Diagnosing
Alzheimer's Disease. 17. Combination of sensors-based monitoring system and
internet of things (IoT): A survey and framework for remote and intensive
care unit patients. 18. End-to end solutions for the Remote Monitoring of
Post-operative Prehabilitation program: IoT solution challenges.
Synergy and Biomarker Values. 2. EMG Feature Extraction Based on
Cardinality with Deep Learning Concepts. 3. Surface Electromyography
Sensors for Human Activity Recognition: Recent Advancements and
Perspectives. 4. ECG signal monitoring and processing in the operating
room. 5. Photoplethysmography and Inertial Sensors in Wearable Devices for
Healthcare: Multimodal Signal Processing for Increasing Accuracy. 6.
Non-invasive system for measuring parameters relevant to sleep quality and
detecting sleep diseases: The data model. 7. PREDICTING INCIDENCE OF STROKE
VIA SUPERVISED MACHINE LEARNING METHODS ON CLASS IMBALANCED DATA. 8.
Ultrasound vector flow imaging, a promising technique towards a new carotid
atheroma risk stratification. 9. A Pre-screening Technique for Coronary
Artery Disease with Multi-channel Phonocardiography and
Electrocardiography. 10. Exploring the feasibility of estimating the
carotid-to-femoral pulse wave velocity using machine learning algorithms.
11. DVT Diagnosis based on HOS & Scattering Operators. 12. Non-invasive
AI-assisted Techniques for 3D Printing of the Heart via Image Analysis:
Current State, Challenges, and Future Directions. 13. COVID-19 and
Pneumonia Detection System using Deep Learning with Chest X-ray Images. 14.
Scattering Operators and high order statistics along with Elastography to
Identify & Characterize Salivary Gland Abnormalities. 15. SA-SVM
Classification-Based Smart Feature Selection Algorithm for Skin Cancer
Detection. 16. A Review on Advanced CNN Architecture in Diagnosing
Alzheimer's Disease. 17. Combination of sensors-based monitoring system and
internet of things (IoT): A survey and framework for remote and intensive
care unit patients. 18. End-to end solutions for the Remote Monitoring of
Post-operative Prehabilitation program: IoT solution challenges.
1. Upper Limb Recovery Prediction Based on Multilevel Mixed Effect EMG
Synergy and Biomarker Values. 2. EMG Feature Extraction Based on
Cardinality with Deep Learning Concepts. 3. Surface Electromyography
Sensors for Human Activity Recognition: Recent Advancements and
Perspectives. 4. ECG signal monitoring and processing in the operating
room. 5. Photoplethysmography and Inertial Sensors in Wearable Devices for
Healthcare: Multimodal Signal Processing for Increasing Accuracy. 6.
Non-invasive system for measuring parameters relevant to sleep quality and
detecting sleep diseases: The data model. 7. PREDICTING INCIDENCE OF STROKE
VIA SUPERVISED MACHINE LEARNING METHODS ON CLASS IMBALANCED DATA. 8.
Ultrasound vector flow imaging, a promising technique towards a new carotid
atheroma risk stratification. 9. A Pre-screening Technique for Coronary
Artery Disease with Multi-channel Phonocardiography and
Electrocardiography. 10. Exploring the feasibility of estimating the
carotid-to-femoral pulse wave velocity using machine learning algorithms.
11. DVT Diagnosis based on HOS & Scattering Operators. 12. Non-invasive
AI-assisted Techniques for 3D Printing of the Heart via Image Analysis:
Current State, Challenges, and Future Directions. 13. COVID-19 and
Pneumonia Detection System using Deep Learning with Chest X-ray Images. 14.
Scattering Operators and high order statistics along with Elastography to
Identify & Characterize Salivary Gland Abnormalities. 15. SA-SVM
Classification-Based Smart Feature Selection Algorithm for Skin Cancer
Detection. 16. A Review on Advanced CNN Architecture in Diagnosing
Alzheimer's Disease. 17. Combination of sensors-based monitoring system and
internet of things (IoT): A survey and framework for remote and intensive
care unit patients. 18. End-to end solutions for the Remote Monitoring of
Post-operative Prehabilitation program: IoT solution challenges.
Synergy and Biomarker Values. 2. EMG Feature Extraction Based on
Cardinality with Deep Learning Concepts. 3. Surface Electromyography
Sensors for Human Activity Recognition: Recent Advancements and
Perspectives. 4. ECG signal monitoring and processing in the operating
room. 5. Photoplethysmography and Inertial Sensors in Wearable Devices for
Healthcare: Multimodal Signal Processing for Increasing Accuracy. 6.
Non-invasive system for measuring parameters relevant to sleep quality and
detecting sleep diseases: The data model. 7. PREDICTING INCIDENCE OF STROKE
VIA SUPERVISED MACHINE LEARNING METHODS ON CLASS IMBALANCED DATA. 8.
Ultrasound vector flow imaging, a promising technique towards a new carotid
atheroma risk stratification. 9. A Pre-screening Technique for Coronary
Artery Disease with Multi-channel Phonocardiography and
Electrocardiography. 10. Exploring the feasibility of estimating the
carotid-to-femoral pulse wave velocity using machine learning algorithms.
11. DVT Diagnosis based on HOS & Scattering Operators. 12. Non-invasive
AI-assisted Techniques for 3D Printing of the Heart via Image Analysis:
Current State, Challenges, and Future Directions. 13. COVID-19 and
Pneumonia Detection System using Deep Learning with Chest X-ray Images. 14.
Scattering Operators and high order statistics along with Elastography to
Identify & Characterize Salivary Gland Abnormalities. 15. SA-SVM
Classification-Based Smart Feature Selection Algorithm for Skin Cancer
Detection. 16. A Review on Advanced CNN Architecture in Diagnosing
Alzheimer's Disease. 17. Combination of sensors-based monitoring system and
internet of things (IoT): A survey and framework for remote and intensive
care unit patients. 18. End-to end solutions for the Remote Monitoring of
Post-operative Prehabilitation program: IoT solution challenges.