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Biomedical Signal Processing

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Cover of 'Biomedical Signal Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations
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    Chapter 2 Estimation of Ankle Joint Torque and Angle Based on S-EMG Signal for Assistive Rehabilitation Robots
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    Chapter 3 Force Myography and Its Application to Human Locomotion
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    Chapter 4 Comparison of Independence of Triceps Brachii and Biceps Brachii Between Paretic and Non-paretic Side During Different MVCs—A Case Study
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    Chapter 5 An EEG Brain-Computer Interface to Classify Motor Imagery Signals
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    Chapter 6 Using Artificial Neural Networks on Multi-channel EEG Data to Detect the Effect of Binaural Stimuli in Resting State
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    Chapter 7 Automated Detection of Seizure and Nonseizure EEG Signals Using Two Band Biorthogonal Wavelet Filter Banks
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    Chapter 8 Automated Identification of Epileptic Seizures from EEG Signals Using FBSE-EWT Method
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    Chapter 9 DWT Based Time Domain Features on Detection of Epilepsy Seizures from EEG Signal
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    Chapter 10 Unipolar Cardiac Leads Between History and Science
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    Chapter 11 Novel Methodology for Cardiac Arrhythmias Classification Based on Long-Duration ECG Signal Fragments Analysis
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    Chapter 12 Artificial Intelligence-Enabled ECG Big Data Mining for Pervasive Heart Health Monitoring
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    Chapter 13 The Power of Tensor-Based Approaches in Cardiac Applications
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    Chapter 14 Syntactic Methods for ECG Signal Diagnosis and QRS Complexes Recognition
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    Chapter 15 Extraction of ECG Significant Features for Remote CVD Monitoring
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    Chapter 16 An Accelerated Computational Approach in Proteomics
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Title
Biomedical Signal Processing
Published by
Springer Singapore, November 2019
DOI 10.1007/978-981-13-9097-5
ISBNs
978-9-81-139096-8, 978-9-81-139097-5
Editors

Naik, Ganesh

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Researcher 1 25%
Student > Postgraduate 1 25%
Readers by discipline Count As %
Engineering 3 75%
Computer Science 1 25%
Mathematics 1 25%