
Biosignal Processing and Classification Using Computational Learning and Intelligence
1st Edition
Principles, Algorithms and Applications
Secure Checkout
Personal information is secured with SSL technology.Free Shipping
Free global shippingNo minimum order.
Description
Biosignal Processing and Classification Using Computational Learning and Intelligence: Principles, Algorithms and Applications posits an approach for biosignal processing and classification using computational learning and intelligence, highlighting that the term biosignal refers to all kinds of signals that can be continuously measured and monitored in living beings. The book is composed of four relevant parts. Part One is an introduction to biosignals and their processing. Part Two presents the fundamentals of computational learning (machine learning). Then, the main techniques of computational intelligence are described along with the hybrid systems, which are the resulting combinations of these techniques. The authors focus primarily on the explanation of the most used methods in the last part of this book, which is the most extensive portion of the book. This part consists of a recapitulation of the newest applications in which these techniques have been successfully applied to the biosignals’ domain, including EEG-based Brain-Computer Interfaces (BCI), emotion recognition from voice, leukemia recognition, infant cry recognition, epilepsy diagnosis from EEG, and automatic smell recognition.
Key Features
- Provides coverage of the fundamentals of signal processing, including sensing the heart, sending the brain, sensing human acoustic, and sensing other organs
- Includes coverage biosignal pre-processing techniques such as filtering, artifiact removal, and feature extraction techniques such as Fourier transform, wavelet transform, and MFCC
- Covers the latest techniques in machine learning and computational intelligence, including Supervised Learning, common classifiers, feature selection, dimensionality reduction, fuzzy logic, neural networks, Deep Learning, bio-inspired algorithms, and Hybrid Systems
- Written by engineers to help engineers, computer scientists, researchers, and clinicians understand the technology and applications of computational learning to biosignal processing
Readership
Biomedical Engineers and researchers in neural engineering, medical imaging, machine learning, neural networks, and computational intelligence. Students, researchers and clinicians in oncology, epilepsy, and a variety of other specialties
Table of Contents
Part I Biosignals
1. Signals and Biosignals
2. Sensing the Heart
3. Sensing the Brain
4. Sensing Human Acoustics
5. Sensing Other Organs
6. Biosignal Processing
Part II Machine Learning
7. Supervised Learning
8. Common Classifiers
9. Feature Selection and Dimensionality Reduction
10. Assessing Classifier's Performance
Part III Computational Intelligence
11. Fuzzy Logic
12. Neural Networks
13. Bio-Inspired Algorithms
14. Hybrid Systems
Part IV Applications
15. EEG-Based Brain-Computer Interfaces (BCIs)
16. Emotion Recognition from Voice
17. Leukemia Recognition
18. Infant Cry Recognition
19. Epilepsy Diagnosis from EEG
20. Towards Automatic Smell Recognition
Details
- No. of pages:
- 432
- Language:
- English
- Copyright:
- © Academic Press 2021
- Published:
- 1st October 2021
- Imprint:
- Academic Press
- Paperback ISBN:
- 9780128201251
About the Authors

Alejandro Torres Garcia
Collaborator in the project “New alternatives of analysis and interpretation for functional optical neuroimage”. Instituto Nacional de Astrofísica Óptica y Electrónica. Puebla, Mexico. Main activity: First steps towards the design of an ontology for the analysis and experimentation in Functional Near Infrared Spectroscopy (OntoNIRS). This includes the computing of main possible terms from literature’s papers (based on n-grams extraction using Python), evaluation/reuse of available ontologies, and finally both the design of a preliminary taxonomy and the obtaining of preliminary rules of OntoNIRS. Supervised by Dr. Felipe Orihuela-Espina Sep 2011–Jun 2012 Teacher of differential and integral calculus, Informatics II, Computing II. Instituto Universitario Puebla (IUP). Puebla, Puebla. Sep 2011–Oct 2011 Collaboratorintheproject“Methodsandtechniquesofcomputationalintelligenceanddata mining for solutions’ analysis and decision-making in mature oil fields”. Instituto Nacional de Astrofísica Óptica y Electrónica. Puebla, Mexico. Main activity: Developing a tool (in Java Core) for applying statistical tests to the obtained performances of automatic classifiers. Supervised by Dr. Luis Villaseñor-Pineda Jul–Dec 2005 Developer in the computing department. Grupo Inmobiliario Mesoamericano S.A. (GRIMSA). Tuxtla Gutiérrez, Chiapas. Main activity: Developing a tool (in Visual Fox-Pro) to record and query the state of the pipelines in the homes of Tuxtla Gutiérrez. Dr. Alejandro Torres-Garcia is a Research Project Collaborator at the Instituto Nacional de Astrofísica Óptica y Electrónica. Puebla, Mexico. He holds a Ph.D. in Computer Science from the same Institute. He is currently a research collaborator in the project “New alternatives of analysis and interpretation for functional optical neuroimage,” which has as its main objective developing the first steps towards the design of an ontology for the analysis and experimentation in Functional Near Infrared Spectroscopy (OntoNIRS). This includes the computing of main possible terms from the literature’s papers (based on n-grams extraction using Python), evaluation/reuse of available ontologies, and, finally, both the design of a preliminary taxonomy and the obtaining of preliminary rules of OntoNIRS.
Affiliations and Expertise
Research Project Collaborator, Instituto Nacional de Astrofísica Optica y Electronica, Puebla, Mexico

Carlos Reyes Garcia
Carlos Alberto Reyes Garcia has a PhD degree in Computer Sciences with specialty in Artificial Intelligence from the Florida State University in Tallahassee, Florida, April 1994. He also has the MSc in Computer Sciences and the MSc in Engineering Management from the Florida Institute of Technology, in Melbourne, Florida June 1984 and August 1984 respectively. He has done a postdoctoral research staying as a visiting professor at the Istituto Internazionale per gli Alti Studi Scientifici (IIASS-E.R. Caianiello) in the city of Vietri sul Mare, Salerno, Italia (Feb. 1999Jan. 2000). At present he is a full time researcher at the Department of Computer Science of the Instituto Nacional de Astrofisica Optica y ElectronicaINAOE in Puebla, Mexico. He is a National Researcher Level II at the Mexican National Researchers System. He was the President of the Executive Board of the Mexican Society for Artificial Intelligence (SMIA) for the period 2008-2010. His research interest areas are; Intelligent Systems, Fuzzy Sets and Logic, Fuzzy Neural Networks, Genetic Algorithms, Computational Intelligence, Biosignals Processing and Classification, Automatic Speech and Speaker Recognition, Infant Cry Recognition and General Pattern Classification. He has been director of 10 bachelor thesis, 21 master's and seven doctoral. He has published over 160 articles in scientific journals and proceedings of national and international conferences, 18 book chapters and edited 16 books. Dr. Carlos Reyes-Garcia is a full-time researcher in the Department of Computer Science at the Instituto Nacional de Astrofisica Optica y Electronica in Puebla, Mexico. He holds a Ph.D. in Computer Science with a specialty in Artificial Intelligence from Florida State University, Tallahassee, Florida, USA. He is a National Researcher Level II in the Mexican National Researchers System. He was the President of the Executive Board of the Mexican Society for Artificial Intelligence (SMIA) for the period 2008-2010. His research interest areas are; Intelligent Systems, Fuzzy Sets and Logic, Fuzzy Neural Networks, Genetic Algorithms, Computational Intelligence, Biosignals Processing and Classification, Automatic Speech and Speaker Recognition, Infant Cry Recognition and General Pattern Classification.
Affiliations and Expertise
Full-Time Researcher, Department of Computer Science, Instituto Nacional de Astrofisica Optica y Electronica, Puebla, Mexico

Luis Villasenor-Pineda
Dr. Luis Villasenor-Pineda is Lead Researcher in the Department of Computer Science at the Instituto Nacional de Astrofisica Optica y Electronica in Puebla, Mexico. He holds a Ph.D. in Computer Science from Université Joseph Fourier, France. Laboratory CLIPS Communication Langagière et Communication Personne-Système, IMAG Institut d’Informatique et Mathématiques Appliquées de Grenoble. France. He currently serves as Coordinator of the Language Technologies Academic Section, Academia Mexicana de Ciencias Computacionales (AMEXCOMP), and as President of the Mexican Association for Natural Language Processing (AMPLN).
Affiliations and Expertise
Lead Researcher, Department of Computer Science, Instituto Nacional de Astrofisica Optica y Electronica in Puebla, Mexico

Omar Montoya
Dr. Omar Mendoza Montoya, is a Researcher at the Freie Universitat Berlin, Germany. He holds a Ph.D. in Computer Science from the Freie Universitat Berlin. His research interests include development of a hybrid brain-computer interface for autonomous systems, analysis of power changes in electrical brain signals by using the time-frequency decomposition, development of mobile neurofeedback applications and brain-computer interfaces, as well as design and implementation of real-time visualizations for electrical neural activity. Summary of Qualifications • A five-year doctorate program in computer science. • A two-year full-time postgraduate program in computer science. • Five years of studies in electronics. • One year working as a research collaborator at Charité Universitätsmedizin Berlin. • Two years working as a research assistant at CIMAT (Investigation Center in Mathematics, Mexico). • Two years of professional experience working in the automotive sector as a programmer of test systems for electronic devices. • Strong knowledge of computational methods for applied statistics, pattern recognition, digital signal processing, and numerical optimization. • Fluent in programming languages (C/C++, C#, Java, Python, Visual Basic), as well as a domain in specialized languages (Matlab, R, Mathematica). Good experience in web technologies (HTML, XHTML, CSS, XML, JavaScript, ASP.NET) and databases (MySQL). • Experience in parallel and high-performance computing application development. Education 2012-2017 Ph.D. in Computer Science. Freie Universität Berlin, Germany. Thesis: Development of a hybrid brain-computer interface for autonomous systems. 2008-2010 Master’s degree in Computer Science. Investigation Center in Mathematics, Guanajuato, Mexico. Thesis: Analysis of power changes in electrical brain signals by using the time-frequency decomposition. 2001-2006 Engineer in Electronics. Instituto Tecnológico de Chihuahua, Mexico. 1998-2001 High school Diploma. Colegio de Bachilleres Plantel 4, Chihuahua, Mexico. Additional Qualifications • Diploma, curse for trainers of the Mexican Mathematics Olympiad, 2001, 20 hours. Professional Experience Charité Universitätsmedizin Berlin, September 2016 – Present • Development of mobile neurofeedback applications and brain-computer interfaces. • Design and implementation of real-time visualizations for electrical neural activity. Investigation Center in Mathematics (CIMAT), August 2010 – August 2012 • Design and implementation of statistical software for multidimensional signal processing. • Development of multiple testing procedures and regression techniques for high dimensional problems. • Implementation of visualization techniques for electrophysiological data. Instituto Nacional de Antropología e Historia (INAH), August 2010 – August 2012 • Development of a software platform for 3D matching of archeological objects. • Design of a web platform to control the inventory of archeological pieces of the “Museo de Sitio” in Palenque, Chiapas. Visteon Mexico Technical Center, August 2006 – July 2008 • Development of testing equipment for powertrain control modules. • Design and testing of new hardware for measurement applications. • Programming of software routines for test systems.
Affiliations and Expertise
Researcher, Freie Universitat Berlin, Germany
Ratings and Reviews
Request Quote
Tax Exemption
Elsevier.com visitor survey
We are always looking for ways to improve customer experience on Elsevier.com.
We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.
If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website.
Thanks in advance for your time.