Information Theory and Entropy in Biosignal
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Signal and Data Analysis".
Deadline for manuscript submissions: closed (27 October 2022) | Viewed by 517
Special Issue Editor
Interests: neural engineering; brain–computer interface; neural and biomedical signal processing; information-theoretic machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the advent of sensing and computing technologies, biosignals have increased significance in diverse applications such as clinical diagnosis/prognosis, wearable devices, human–machine interaction, etc. The human’s behaviors are represented as various biosignals: electroencephalography (EEG), electrocorticography (ECoG), and magnetoencephalograms (MEGs) as the brain’s activity, electrocardiograms (ECGs) as the activity of the heart, electromyograms (EMGs) as muscle movement. Interpreting biosignals has long rendered insights into physiology, disease, and healthcare. Obtaining valuable and useful information in biosignals is still the main research issue. Over the past few decades, information theory and entropy have offered considerable contributions in the analysis of biosignals. Understanding various physiological systems by interpreting biosignals remains a challenge with the expanded use of biosignals.
The main goal of this Special Issue, “Information Theory and Entropy in Biosignals”, is to disseminate original novel research papers and attract significant contributions in the research field of information theory and entropy analysis of biosignals from the theoretical part to practical use.
Prof. Dr. Young-Seok Choi
Guest Editor
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Keywords
- information theory and entropy analysis of biosignals (EEG, ECoG, MEG, EMG, ECG, PPG, EOG, respiration rate, electrodermal activity, etc.)
- multiscale entropy analysis of biosignals
- multivariate entropy analysis of biosignals
- functional connectivity via transfer entropy of biosignals
- information theory and entropy analysis for multimodal biosignals
- information-theoretic learning for biosignals
- information theory and entropy analysis for medical imaging (CT, MRI, PET, SPECT, etc.)
- emerging applications of information theory and entropy in biosignals
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