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ABOUT THE BOOK

This book presents the theoretical basis and applications of biomedical signal analysis and processing. Initially, the nature of the most common biomedical signals, such as electroencephalography, electromyography, electrocardiography and others, is described. The theoretical basis of linear signal processing is summarized, with continuous and discrete representation, linear filters and convolutions, Fourier and Wavelets transforms. Machine learning concepts are also presented, from classic methods to deep neural networks. Finally, several applications in neuroscience are presented and discussed, involving diagnosis and therapy, in addition to other applications.

Features:

• Explains signal processing of neuroscience applications using modern data science techniques.

• Provides comprehensible review on biomedical signals nature and acquisition aspects.

• Focusses on selected applications of neurosciences, cardiovascular and muscle-related biomedical areas.

• Includes computational intelligence, machine learning and biomedical signal processing and analysis.

• Reviews theoretical basis of deep learning and state-of-the-art biomedical signal processing and analysis.

This book is aimed at researchers, graduate students in biomedical signal processing, signal processing, electrical engineering, neuroscience and computer science.

TABLE OF CONTENTS

SECTION 1 Physiological Signal Processing—Challenges

1. Signal Processing for Understanding Physiological Mechanisms for Information Decoding
P. Geethanjali

2. Automated Recognition of Alzheimer’s Dementia: A Review of Recent Developments in the Context of Interspeech ADReSS Challenges
Muhammad Shehram Shah Syed, Zafi Sherhan Syed, Margaret Lech and Elena Pirogova

3. Electrogastrogram Signal Processing: Techniques and Challenges with Application for Simulator Sickness Assessment
Nadica Miljković, Nenad B. Popović, and Jaka Sodnik

4. Impact of Cognitive Demand on the Voice Responses of Parkinson’s Disease and Healthy Cohorts
Rekha Viswanathan and Sridhar P. Arjunan

SECTION 2 EEG—ECG Signal Processing

5. Electroencephalography and Epileptic Discharge Identification
Mohd Syakir Fathillah, Theeban Raj Shivaraja, Khalida Azudin and Kalaivani Chellappan

6. A Novel End-to-End Secure System for Automatic Classification of Cardiac Arrhythmia
Narendra K. C., Pradyumna G. R. and Roopa B. Hegde

7. Machine Learning for Detection and Classification of Motor Imagery in Electroencephalographic Signals
Juliana C. Gomes, Vanessa Marques, Caio de Brito, Yasmin Nascimento, Gabriel Miranda, Nathália Córdula, Camila Fragoso, Arianne Torcarte, Maíra A. Santana, Giselle Moreno and Wellington Pinheiro dos Santos

8. Emotion Recognition from Electroencephalographic and Peripheral Physiological Signals Using Artificial Intelligence with Explicit Features
Maíra A. Santana, Juliana C. Gomes, Arianne S. Torcate, Flávio S. Fonseca, Amanda Suarez, Gabriel M. Souza, Giselle M. M. Moreno and Wellington Pinheiro dos Santos

9. Identification of Emotion Parameters in Music to Modulate Human Affective States: Towards Emotional Biofeedback as a Therapy Support
Maíra A. Santana, Ingrid B. Nunes, Flávio S. Fonseca, Arianne S. Torcate, Amanda Suarez, Vanessa Marques, Nathália Córdula, Juliana C. Gomes, Giselle M. M. Moreno and Wellington Pinheiro dos Santos

SECTION 3 Gait—Balance Signal Processing

10. Updated ICA Weight Matrix for Lower Limb Myoelectric Classification
Ganesh R. Naik

11. Cortical Correlates of Unilateral Transfemoral Amputees during a Balance Control Task with Vibrotactile Feedback
Aayushi Khajuria, Upinderpal Singh and Deepak Joshi

12. Assessing the Impact of Body Mass Index on Gait Symmetry of Able-Bodied Adults Using Pressure-Sensitive Insole
Maria Rashid, Asim Waris, Syed Omer Gilani, Faddy Al-Najjar, Amit N. Pujari and Imran Khan Niazi

13. Analysis of Lower Limb Muscle Activities during Walking and Jogging at Different Speeds
Ganesh R. Naik

SECTION 4 Wearables—Sensors Signal Processing

14. Biosensors in Optical Devices for Sensing and Signal Processing Applications
Shwetha M. and Ganesh R. Naik