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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.
- 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
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
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
- No. of pages:
- © Academic Press 2021
- 1st October 2021
- Academic Press
- Paperback ISBN:
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.
Research Project Collaborator, Instituto Nacional de Astrofísica Optica y Electronica, Puebla, Mexico
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.
Full-Time Researcher, Department of Computer Science, Instituto Nacional de Astrofisica Optica y Electronica, Puebla, Mexico
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).
Lead Researcher, Department of Computer Science, Instituto Nacional de Astrofisica Optica y Electronica in Puebla, Mexico
Researcher, Freie Universitat Berlin, Germany
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