Biomedical Signal Processing Advances in Theory, Algorithms and Applications / [electronic resource] :
edited by Ganesh Naik.
- 1st ed. 2020.
- X, 432 p. 237 illus., 125 illus. in color. online resource.
- Series in BioEngineering, 2196-887X .
- Series in BioEngineering, .
Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations -- Estimation of ankle joint torque and angle based on S-EMG signal for assistive rehabilitation robots -- Force Myography and its Application to Human Locomotion -- Comparison of Independence of Triceps Brachii and Biceps Brachii between Paretic and Non-Paretic side during different MVCs–A case study -- An EEG brain-computer interface to classify motor imagery signals.
This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing. .
9789811390975
10.1007/978-981-13-9097-5 doi
Biomedical engineering.
Signal processing.
Pattern recognition systems.
Computational intelligence.
Mathematics—Data processing.
Artificial intelligence.
Biomedical Engineering and Bioengineering.
Signal, Speech and Image Processing .
Automated Pattern Recognition.
Computational Intelligence.
Computational Mathematics and Numerical Analysis.
Artificial Intelligence.
R856-857
610.28
Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations -- Estimation of ankle joint torque and angle based on S-EMG signal for assistive rehabilitation robots -- Force Myography and its Application to Human Locomotion -- Comparison of Independence of Triceps Brachii and Biceps Brachii between Paretic and Non-Paretic side during different MVCs–A case study -- An EEG brain-computer interface to classify motor imagery signals.
This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing. .
9789811390975
10.1007/978-981-13-9097-5 doi
Biomedical engineering.
Signal processing.
Pattern recognition systems.
Computational intelligence.
Mathematics—Data processing.
Artificial intelligence.
Biomedical Engineering and Bioengineering.
Signal, Speech and Image Processing .
Automated Pattern Recognition.
Computational Intelligence.
Computational Mathematics and Numerical Analysis.
Artificial Intelligence.
R856-857
610.28