Advanced Methods in Biomedical Signal Processing and Analysis

Langue : Anglais

Coordonnateurs : Pal Kunal, Ari Samit, Bit Arindam, Bhattacharyya Saugat

Couverture de l’ouvrage Advanced Methods in Biomedical Signal Processing and Analysis

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Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques.

1. Feature engineering 2. Heart rate variability 3. Understanding the suitabillity of parametric modeling techniques in detecting the changes in the HRV signals acquired from cannabis consuming and nonconsuming Indian paddy-field workers 4. Patient-specific ECG beat classification using EMD and deep learning-based technique 5. Empirical wavelet transform and deep learning-based technique for ECG beat classification 6. Development of an Internet-of-Things (IoT)-based pill monitoring device for geriatric patients 7. Biomedical robotics 8. Combating COVID-19 by implying machine learning predictions and projections 9. Deep learning methods for analysis of neural signals: From conventional neural network to graph neural network 10. Improved extraction of the extreme thermal regions of breast IR images 11. New metrics to asses the subtle changes of the heart's electromagnetic field 12. The role of optimal and modified lead systems in electrocardiogram 13. Adaptive rate EEG processing and machine learning-based efficient recognition of epilepsy 14. Multimodal microscopy: A novel low-cost microscope designed for food and biological applications

Dr. Kunal Pal is currently the professor-in-charge of Medical Electronics and Instrumentation Laboratory in the Department of Biotechnology and Medical Engineering, National Institute of Technology, India. His major research interests revolve around biomedical signal processing, biomedical equipment design, soft materials, and controlled drug delivery. He has published more than 100 publications in SCI-cited journals of high repute.
Dr. Samit Ari received B. Tech in Electronics and Tele-communication Engineering degree from University of Kalyani and M. Tech degree in Instrumentation Engineering from University of Calcutta. He completed Ph.D in Electronics and Electrical Communication Engineering from Indian Institute of Technology (IIT), Kharagpur. He joined National Institute of Technology (NIT) Rourkela as a faculty member in 2009, where he presently holds the position of Associate Professor in the department of Electronics and Communication Engineering. He is an accomplished researcher with strong research background in Signal Processing, Image processing, Data Modeling, Biomedical Signal and Image Processing, Pattern Recognition and Artificial Intelligence. Currently, he is Professor-in-charge of Pattern Recognition and Machine Intelligence Lab, Dept. of Electronics and Communication Enginnering, NIT Rourkela. Dr. Ari is a member of IEEE and IEEE signal processing society. Currently, he is also Associate Editor of IET Image Processing Journal. He has published more than sixty research articles in reputed journals (like IEEE, IET, Elsevier, Springer etc.) and conferences. He has guided four PhD, and supervised more than fifty M. Tech and more than forty B. Tech projects. He handles number of projects funded by DRDO, SERB etc. in the area of Signal and Image processing, Artificial Intelligence. He is a reviewer of IEEE, IET, Elsevier and other international journal papers.
He received his PhD in Biofluidic Engineering at Jadavpur University, India in 2016.