Computational and Mathematical Methods in Medicine

Advanced Signal Processing for Cardiovascular and Neurological Diseases


Status
Published

Lead Editor

1Anglia Ruskin University, Chelmsford, UK

2Southern University of Science and Technology, Shenzhen, China

3Harvard Medical School, Boston, USA

4National Taiwan University of Science and Technology, Taipei, Taiwan


Advanced Signal Processing for Cardiovascular and Neurological Diseases

Description

Advanced signal processing and computing techniques have been consistently playing a significant role in the field of biomedical engineering research. This special issue will focus on the use and elaboration of latest techniques, like deep machine learning, compressed sensing, nonlinear dynamical approaches, and so on, to analyze biomedical data relevant for understanding and treatment of cardiovascular and neurological diseases.

More specifically, these advanced techniques are applied to ECG, EEG, arterial pulse, heart sounds, impedance and respiratory signals, plethysmography and transcranial Doppler, near infrared spectroscopy, and so on. The special issue will be an international forum for researchers working in the fields of biomedical engineering, medical physics, computational neuroscience, and integrative physiology to report the most recent developments and ideas, with special emphasis on the following research topics.

Potential topics include but are not limited to the following:

  • Noise suppression and removal in analyzing cardiovascular and neurophysiological signals
  • Nonlinear dynamical approaches and multivariate and multiscale techniques for analyzing cardiovascular and neurophysiological signals
  • Application of machine learning and deep neural networks for detection and classification of cardiovascular and neurological diseases
  • Advanced signal processing for the interactions between cardiovascular and neurological diseases
  • Advanced signal processing in brain-computer interface and neuroprosthetic devices
  • Acquisition and analysis of cardiovascular and neurophysiological signals from mobile and wearable devices and body sensor network techniques

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 3416540
  • - Editorial

Advanced Signal Processing for Cardiovascular and Neurological Diseases

Dingchang Zheng | Fei Chen | ... | Sheng-Yu Peng
  • Special Issue
  • - Volume 2018
  • - Article ID 2396952
  • - Research Article

An Intelligent Parkinson’s Disease Diagnostic System Based on a Chaotic Bacterial Foraging Optimization Enhanced Fuzzy KNN Approach

Zhennao Cai | Jianhua Gu | ... | Huiling Chen
  • Special Issue
  • - Volume 2018
  • - Article ID 1482874
  • - Research Article

Common Interferences Removal from Dense Multichannel EEG Using Independent Component Decomposition

Weifeng Li | Yuxiaotong Shen | ... | Yun Ge
  • Special Issue
  • - Volume 2018
  • - Article ID 3675974
  • - Research Article

Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones

Linfei Ge | Jin Zhang | Jing Wei
  • Special Issue
  • - Volume 2018
  • - Article ID 3543048
  • - Research Article

Does the Temporal Asymmetry of Short-Term Heart Rate Variability Change during Regular Walking? A Pilot Study of Healthy Young Subjects

Xinpei Wang | Chang Yan | ... | Peng Li
  • Special Issue
  • - Volume 2018
  • - Article ID 4254189
  • - Research Article

Kernel Principal Component Analysis of Coil Compression in Parallel Imaging

Yuchou Chang | Haifeng Wang
  • Special Issue
  • - Volume 2018
  • - Article ID 7108906
  • - Research Article

Scenario Screen: A Dynamic and Context Dependent P300 Stimulator Screen Aimed at Wheelchair Navigation Control

Omar Piña-Ramirez | Raquel Valdes-Cristerna | Oscar Yanez-Suarez
  • Special Issue
  • - Volume 2018
  • - Article ID 6812404
  • - Research Article

Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography

William Waugh | John Allen | ... | Thomas A. W. Beale
  • Special Issue
  • - Volume 2018
  • - Article ID 7429782
  • - Research Article

Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease

Xiaoli Liu | Peng Cao | ... | Dazhe Zhao
  • Special Issue
  • - Volume 2017
  • - Article ID 2948742
  • - Research Article

Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI

Rong Liu | Yongxuan Wang | ... | Jun Cheng
Computational and Mathematical Methods in Medicine
 Journal metrics
Acceptance rate32%
Submission to final decision46 days
Acceptance to publication39 days
CiteScore3.400
Impact Factor1.770
 Submit