This book provides an insightful review and methodological contribution about future healthcare system. It also provides a space for creating and designing techniques for effective sensing, processing, and analysis of patient health situations based on bio-signal processing. Additionally, it discusses novel methods and algorithms which are needed to overcome limitations in current rhythmic bio-signals models. It also discusses solutions and systems needed to efficiently evaluate and process real-time data. The book is useful for wide range of users, including students, research scientists, teachers, and practitioners working in the field of heath informatics, neuroscience, biomedical engineering, and medical image processing and diagnosis.

Discusses novel methods and algorithms needed to overcome limitations in current rhythmic bio-signals models Includes modeling and rhythmic biological signals (EEG, EMG, MEG, ECG, and PCG) collected from human health Presents case studies and directives for unique approaches for advanced healthcare systems

Autorentext

Dr. Kaiser M. Shamim is currently working as Professor at the Institute of Information Technology of Jahangirnagar University, Savar, Dhaka-1342, Bangladesh. He received his Bachelor's and Master's degrees in Applied Physics Electronics and Communication Engineering from the University of Dhaka, Bangladesh, in 2002 and 2004, respectively, and the Ph.D. degree in Telecommunication Engineering from the Asian Institute of Technology, Thailand, in 2010. His current research interests include data analytics, machine learning, wireless network & signal processing, cognitive radio network, big data and cyber security, and renewable energy. He has authored more than 140 papers in different peer-reviewed journals and conferences. He is Associate Editor of the IEEE Access Journal, Guest Editor of Brain Informatics Journal, and Cognitive Computation Journal. Dr. Kaiser is Life Member of Bangladesh Electronic Society; Bangladesh Physical Society. He is also Senior Member of IEEE, USA, and IEICE, Japan, and Active Volunteer of the IEEE Bangladesh Section. He is founding Chapter Chair of the IEEE Bangladesh Section Computer Society Chapter. Dr. Kaiser organized various international conferences such as ICEEICT 2015-2018, IEEE HTC 2017, IEEE ICREST 2018, and BI2020.
Dr. Mahmud Mufti is Senior Lecturer of Computing at the Nottingham Trent University, UK. He received Ph.D. degree in Information Engineering from University of Padova, Italy, in 2011. Recipient of the Marie-Curie postdoctoral fellowship, he served at various positions in the industry and academia in India, Bangladesh, Italy, Belgium, and the UK since 2003. Expert in computational intelligence, data analysis, and big data technologies, Dr. Mahmud has published over 80 peer-reviewed articles and papers in leading journal and conferences. Dr. Mahmud serves as Associate Editor to the cognitive computation, IEEE access, big data analytics, and brain informatics journals. Dr. Mahmud is Senior Member of IEEE and ACM, Professional Member of the British Computer Society, and Fellow of the higher education academy, UK. During the year 2020-2021, he is serving as Vice Chair of the Intelligent System Application Technical Committee of IEEE CIS, Member of the IEEE CIS Task Force on Intelligence Systems for Health and the IEEE R8 Humanitarian Activities Subcommittee, and Project Liaison Of cer of the IEEE UK and Ireland SIGHT committee. Dr. Mahmud is also serving as Local Organizing Chair of IEEE-WCCI2020, General Chair of BI2020 and BI2021, and Program Chair of IEEE-CICARE2020.
Mamun Shamim Al received B.Sc. (Hons.) and M.Sc. (Engg.) degrees in Computer Science and Engineering from Jahangirnagar University (JU) and Bangladesh University of Engineering and Technology (BUET), respectively. He also served Head of the Department of Computer Science in Daffodil International University during 2006-2008. He has received his Ph.D. degree in Graduate School of Science and Engineering, Saitama University, Japan, in 2018. His research interests include an autonomous system, arti cial intelligence, and software engineering. He has authored more than 50 research papers in different peer-reviewed international journals and conferences and also worked as Technical Co-chair and Organizing Secretary in ICEEICT and TCCE conference in 2014, 2015, and 2020. Dr. Mamun is also Member of IEEE, USA, and IEICE, Japan.

Inhalt
Is Biological rhythm associated with the mortality of COVID-19?.- Deep Learning in Biomedical devices: Perspectives, Applications and Challenges.- Effect of 3D-Multiple object Tracking training on manual dexterity in elderly adults with dementia and mild cognitive impairment.- Rhythmic Pattern of EEG for Identifying Schizophrenia.- Prior Prediction and Management of Autism in Child through Behavioral Analysis using Machine Learning Approach.- DNN and LiDAR Sensor Based Crowd Avoidance Method for Nurse-Following Robot in Healthcare