AI-Enabled Smart Healthcare Using Biomedical Signals

AI-Enabled Smart Healthcare Using Biomedical Signals

Indexed In: SCOPUS
Release Date: May, 2022|Copyright: © 2022 |Pages: 322
DOI: 10.4018/978-1-6684-3947-0
ISBN13: 9781668439470|ISBN10: 1668439476|EISBN13: 9781668439487
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Description & Coverage
Description:

Technological advancements have enhanced all functions of society and revolutionized the healthcare field. Smart healthcare applications and practices have grown within the past decade, strengthening overall care. Biomedical signals observe physiological activities, which provide essential information to healthcare professionals. Biomedical signal processing can be optimized through artificial intelligence (AI) and machine learning (ML), presenting the next step towards smart healthcare.

AI-Enabled Smart Healthcare Using Biomedical Signals will not only cover the mathematical description of the AI- and ML-based methods, but also analyze and demonstrate the usability of different AI methods for a range of biomedical signals. The book covers all types of biomedical signals helpful for smart healthcare applications. Covering topics such as automated diagnosis, emotion identification, and frequency discrimination techniques, this premier reference source is an excellent resource for healthcare administration, biomedical engineers, medical laboratory technicians, medical technology assistants, computer scientists, libraries, students and faculty of higher education, researchers, and academicians.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Adaptive Data Analysis
  • Advanced Image Decomposition
  • Automated Diagnosis
  • Biomedical Signal Processing
  • Brain Simulation
  • Common Feature Analysis
  • ECG Signal
  • Emotion Identification
  • Frequency Discrimination Techniques
  • Multimedia Learning
  • Neuroimaging Techniques
  • Retinal Fundus Images
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Editor/Author Biographies

Rahul Kumar Chaurasiya received the B. Tech. degree from MANIT Bhopal in 2009, and the M.E. degree from the IISc Bangalore in 2011. He received his Ph.D. degree in 2017 NIT Raipur. He was a Senior Software Engineer with Brocade Communications Systems, Bangalore, in 2011-12. During 2013-19, he was Assistant Professor at the NIT, Raipur. He has served as Assistant Professor Grade-1 at MNIT Jaipur during 2019-20. Since 2020, he is with MANIT Bhopal as Assistant Professor Grade-1. His research area includes Machine Learning, Pattern Recognition, Brain-Computer Interfacing, Optimization, Biomedical Signal Processing. He has authored several research articles in aforementioned areas. He is currently supervising 4 PhD scholars and have supervised 08 M Techs and 50+ B Techs in his area of research.

Dheeraj Agrawal received the B. E. degree from RGTU Bhopal in 2001. He received the M.Tech. and PhD degrees from MANIT Bhopal in 2005 and 2011, respectively. He has more than 20 years of teaching experience and is currently working as Associate Professor at MANIT Bhopal. He is also working as nodal officer at Indian Institute of Information Technology Bhopal. His research area includes Machine Learning, Image processing, and Signal Processing. He has authored several research articles in aforementioned areas. He has supervised 03 PhD scholars and is currently supervising 03 PhD scholars in his area of research.

Ram Bilas Pachori received the B.E. degree with honours in ECE from RGTU, Bhopal, India in 2001, the M.Tech. and Ph.D. degrees in EE from Indian Institute of Technology (IIT) Kanpur, India in 2003 and 2008, respectively. He worked as a Postdoctoral Fellow at Charles Delaunay Institute, University of Technology of Troyes, Troyes, France during 2007-2008. He is presently working as a Professor at IIT Indore. He worked as a Visiting Scholar at Intelligent Systems Research Center, Ulster University, Northern Ireland, UK during December 2014. He is an Associate Editor of Electronics Letters, Biomedical Signal Processing and Control journal and an Editor of IETE Technical Review journal. He is a senior member of IEEE and a Fellow of IETE and IET. He has supervised 12 Ph.D., 20 M.Tech., and 37 B.Tech. students for their theses and projects.

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