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Special Issue "Information Theory and Complexity Science Approaches to Health Conditions and Cognitive Decline"
Deadline for manuscript submissions: closed (30 June 2019).
Department of Electrical and Electronic Engineering, Imperial College London, SW7 2AZ London, UK
Special Issues and Collections in MDPI journals
Special Issue in Entropy: Information Theory Applied to Physiological Signals
The application of information theory to investigate the structural complexity of physiological signals is one of the fastest growing areas in multidisciplinary research, and has the potential to transform lifestyles and healthcare. The related assessment of the deterministic vs stochastic behaviour of the observables also comes with an enormous potential to distinguish between the pathological and a healthy functioning of human organs.
A whole host of approaches do exist to characterise the underlying structural complexity within physiological signals, ranging from entropy-based algorithms to chaotic attractors. These are being gradually applied with the aim to enhance our understanding of the governing mechanisms of the human body, while the so-enabled quantitative assessment of the state of body and mind has enormous potential in transforming both diagnostic methods and the management of chronic illnesses. The scope of using information theory to analyse the (mal-)functioning of the human body is vast, ranging from congestive heart failure, depression, to hydrocephalus and cognitive decline. However, these analyses are still in their infancy, and this Special Issue is an attempt to share the findings on information theory aspects of the assessment of the structural complexity of physiological signals.
The brain, in particular, still remains one of the least understood organs, yet the need to unlock the mysteries of the human brain has never been so pressing. The ageing of the population has led to a rise in cases of cognitive decline, while modern lifestyles have led another pressing issue of chronic stress and depressions experienced by large portions of the population. It is therefore both imperative and timely to explore further the potential of information theory in the early quantification, prevention and management of these issues.
This Special Issue aims to disseminate the latest findings in the investigation and characterisation of health conditions and cognitive decline, using information theory and nonlinear complexity science approaches. We welcome manuscripts presenting novel findings that promise to revolutionise the health and cognitive sciences, in addition to those introducing novel algorithms to quantify the degree of a health-related condition through the assessment of the structural complexity of pathological signals. In particular, we encourage submissions on data acquired from wearable devices, such as ‘hearables’, which are very convenient for the user, but record typically weaker signals, with an overall signal quality that is compromised (due to artefacts or noise).
Prof. Dr. Danilo P. Mandic
Dr. Theerasak Chanwimalueang
Ms. Tricia Adjei
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Electroencephalography for the monitoring and management of health and cognition
- Complexity loss theory for the monitoring and management of health and cognition
- Entropy measures for the monitoring and management of health and cognition
- Computationally efficient entropy measures for pathological bio-signals
- Symbolic dynamics and coding in the health and cognitive sciences
- Markers of cognitive decline in electroencephalography
- Markers of pathology in bio-signals
- Signatures of pathology through information-theory assessment of the deterministic vs. stochastic behaviour of observed physiological signals