Dear Colleague,
the journal Biomedical Signal Processing and Control Journal (IF 3.137,
https://www.journals.elsevier.com/biomedical-signal-processing-and-control)
is currently running a Special Issue entitled “Analysis of 1D Biomedical
signals through AI based approaches for Image processing”, which is now
open for submissions:
https://www.journals.elsevier.com/biomedical-signal-processing-and-control/call-for-papers/special-issue-on-analysis-of-1d-biomedical-signals
Please, find below the Call for Papers of this Special Issue.
I hope it is interesting for you.
I apologize if you received multiple copies of this CFP.
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BIOMEDICAL SIGNAL PROCESSING AND CONTROL JOURNAL
Elsevier - Impact Factor: 3.137
Special Issue on Analysis of 1D Biomedical signals
through AI based approaches for Image processing
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The human body is a complex electro-mechanical system that generates
electrical, mechanical, thermal, and other signals that we normally call
Biomedical Signals. ECG, EMG, PCG, PPG, BCG, skin temperature, and skin
conductance are some of the 1D biomedical signals examples that record the
dynamic changes of the human body, and that can also be monitored by the
use of smart wearables.
The automatic analysis of biomedical signals has become an important
process to both identify indicators of diseased states and to provide
meaningful information for various applications in physiology, sports
medicine and human–computer interface.
Recent advances in Artificial Intelligence (AI) have the potential to
manage and analyze large biomedical datasets leading to the clinical
decisions and real-time applications. These techniques have been applied
successfully to medical imaging, but the analysis of 1D biomedical signals
has yet to fully benefit from this novel approach.
Biomedical Signal and Image Processing include the analysis,
classification, and manipulation of signals by means of operations like
filtering, compression, feature extraction, enhancement and spectral
analysis. Under such conditions, the use of computational innovative
techniques based on the convergence of signal and image processing will
help us to get new solutions to the real-world challenges.
This Special Issue is aimed at sharing the innovative ideas and algorithms
in the Biomedical Signal and Image processing domain. Precisely, the
objective of this Special Issue is to focus the attention on emerging
methods and techniques based on the transformation of biomedical signals
into images and their processing through AI based image processing
approaches.
With this mission, the principal aim of this Special Issue is to collect
original contributions as either research papers or comprehensive reviews
that address and discuss the impact and relevance of signals and images
processing in research and applicative areas such as:
• Audio and Acoustic Signal Processing
• Cardiovascular Signals Processing
• Medical Signal Acquisition, Analysis and Processing
• Motion Control
• Physiological Processes and Biomedical signal Modeling
• Neural Networks for Biomedical Data
• Pattern Recognition & Machine Learning for Biomedical Data
• Biomedical signals from wearable sensors and systems
• Real-Time Systems & Biomedical-Based User Interfaces
• Internet of Health Things
• Detection and Identification of diseases
• Electromagnetic Fields in Biology and Medicine
• Others
all referred to processing of 1D Biomedical Signals as images.
Guest Editors
Dr. Giovanna Sannino – ICAR - CNR, Italy - gio...@ic...
Dr. Nadia Brancati – ICAR - CNR, Italy - nad...@ic...
Prof. Alfred M. Bruckstein – Dep. of Computer Science, Technion IIT, Haifa,
Israel - fr...@cs...
Dr. Maria Frucci – ICAR - CNR, Italy - mar...@ic...
Prof. Daniel Riccio – University of Naples Federico II, Italy -
dan...@un...
Key Dates
Manuscript submission due: March 30, 2021
First Review Results: June 30, 2021
Final Review and Decision: October 30, 2021
Publication date: 4th Quarter 2021
For all information:
https://www.journals.elsevier.com/biomedical-signal-processing-and-control/call-for-papers/special-issue-on-analysis-of-1d-biomedical-signals
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