Complexity

New Methods for Analyzing Complex Biomedical Systems and Signals


Status
Published

Lead Editor

1University of Belgrade, Belgrade, Serbia

2Temple University, Philadelphia, USA

3Technical University of Sofia, Sofia, Bulgaria


New Methods for Analyzing Complex Biomedical Systems and Signals

Description

Biomedical systems are characterized by high complexity and nonlinear dynamics, having fractal and multifractal nature exhibiting even chaotic behavior. This is expressed particularly, but not exclusively, in different vital signs, brain networks, and neuronal and cardiac activities. New measurement techniques and sensing devices of latest generation enable deeper insight into subtle and complex mechanism of biomedical processes. Unfortunately, biomedical data generate extremely large series, producing difficult technical problems concerning the analysis or processing of such data. Managing, processing, storing, retrieving, and transferring such data are challenging issues and need development of new methods and algorithms that could be implemented in different phases of biomedical data analysis or data mining. Besides the linear processing methods, the nonlinear ones including fractal and multifractal analyses, as well as usage of artificial intelligence methods, take place in analyzing complex biomedical signals. It is expected that combination of nonlinear and linear methods could give us better insight into the nature of these data leading towards the more appropriate solutions to analysis of complex data.

We invite authors to submit original research articles as well as review articles that will illustrate and stimulate the continuing efforts in developing the new methods, algorithms, and tools for modeling, processing, and analyzing complex biomedical signals.

Potential topics include but are not limited to the following:

  • Biomedical system modeling
  • Methods for visualization of biomedical processes
  • Biomedical signal understanding and description
  • Linear methods for biomedical signal processing
  • Nonlinear methods for biomedical signal processing
  • Neural network signal processing
  • Biomedical data classification
  • Biomedical data mining
  • Decision support systems applied to different biomedical signals
  • Fuzzy inference

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 6405121
  • - Editorial

New Methods for Analyzing Complex Biomedical Systems and Signals

Irini Reljin | Zoran Obradović | ... | Valeri Mladenov
  • Special Issue
  • - Volume 2018
  • - Article ID 6740846
  • - Research Article

Factor Analysis for Finding Invariant Neural Descriptors of Human Emotions

Vitor Pereira | Filipe Tavares | ... | Petia Georgieva
  • Special Issue
  • - Volume 2018
  • - Article ID 7514709
  • - Research Article

High-Density Lipoproteins-Associated Proteins and Subspecies Related to Arterial Stiffness in Young Adults with Type 2 Diabetes Mellitus

Xiaoting Zhu | Amy S. Shah | ... | L. Jason Lu
  • Special Issue
  • - Volume 2018
  • - Article ID 9728264
  • - Research Article

Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals

Nebojša Malešević | Dimitrije Marković | ... | Christian Antfolk
  • Special Issue
  • - Volume 2017
  • - Article ID 7120691
  • - Research Article

Sparse Learning of the Disease Severity Score for High-Dimensional Data

Ivan Stojkovic | Zoran Obradovic
  • Special Issue
  • - Volume 2017
  • - Article ID 1232868
  • - Research Article

HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks

Luca Marchetti | Rosario Lombardo | Corrado Priami
  • Special Issue
  • - Volume 2017
  • - Article ID 1580414
  • - Research Article

Identification of S1 and S2 Heart Sound Patterns Based on Fractal Theory and Shape Context

Ana Gavrovska | Goran Zajić | ... | Branimir Reljin
  • Special Issue
  • - Volume 2017
  • - Article ID 2647164
  • - Research Article

Interpolative Boolean Networks

Vladimir Dobrić | Pavle Milošević | ... | Ana Poledica
  • Special Issue
  • - Volume 2017
  • - Article ID 4327175
  • - Research Article

New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor

P. Povalej Bržan | J. A. Gallego | ... | A. Holobar
  • Special Issue
  • - Volume 2017
  • - Article ID 9078541
  • - Research Article

Monitoring Effective Connectivity in the Preterm Brain: A Graph Approach to Study Maturation

M. Lavanga | O. De Wel | ... | S. Van Huffel
Complexity
 Journal metrics
Acceptance rate39%
Submission to final decision75 days
Acceptance to publication54 days
CiteScore2.690
Impact Factor2.591
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