Journal of Healthcare Engineering

Cardiovascular Signal Analysis: Methods and Applications

Publishing date
01 Dec 2021
Submission deadline
23 Jul 2021

Lead Editor

1Taipei Veterans General Hospital, Taipei, Taiwan

2CHU-Charleroi, Charleroi, Belgium

3National Taiwan University of Science and Technology, Taipei, Taiwan

4National Yang-Ming University, Taipei, Taiwan

5National Central University, Taoyuan City, Taiwan

This issue is now closed for submissions.

Cardiovascular Signal Analysis: Methods and Applications

This issue is now closed for submissions.


Cardiovascular signals represent a major source of information to monitor the progression of pathological processes going on inside the body. For instance, hyperacute T waves, ST elevation, negative T waves, and pathologic Q waves are suggestive of acute myocardial infarction; the periodic variations in the time intervals between consecutive heartbeats reveal the autonomic regulation of the patient which in turn can provide information regarding the severity of illness. Furthermore, arterial pulse wave has been one of the most fundamental signals in medicine since ancient times. Pulse wave analysis can be used to detect many disorders of the cardiovascular system, such as hypertension, coronary artery diseases, valvular heart diseases, etc. Finally, non-invasive measurement of cardiac output is very useful in the critical care of hemodynamically unstable patients in the intensive care unit.

Analysis of cardiovascular signals has the following advantages: it is non-invasive; it can be monitored in real-time fashion; it is cost-effective; it can be monitored from a remote location; and the signals can be analyzed to yield many parameters for clinical use. The term “cardiovascular signals” here includes, but is not limited to, electrocardiographic signals, pulse wave velocity, pulse flow, pulse pressure, etc. Because of its potential and advantages, the improvement in methodology and the applications of cardiovascular signal analysis will be promising in the future.

This Special Issue will consider a broad range of topics that cover the analysis of the above-mentioned cardiovascular signals of humans or animals in a healthy state or diseased state. Both original research articles and review articles will be considered. We will consider reviews, mini-reviews, case reports, case series, research articles. Retrospective and prospective studies will also be considered.

Potential topics include but are not limited to the following:

  • Machine learning/deep learning for cardiovascular signal analysis, including the development of artificial intelligence protocols
  • Portable/wearable cardiovascular signal processing devices
  • In vivo and in vitro cardiovascular signal analysis
  • Device and instrumentation for cardiovascular signal analysis
  • Consumer electronics and cardiovascular signal analysis
  • Image-based cardiovascular signal analysis
  • Methodology of cardiovascular signal analysis
  • Modelling and simulation for cardiovascular signal analysis
  • Clinical applications of cardiovascular signal analysis
  • Cardiovascular signal analysis for healthy lighting and display
Journal of Healthcare Engineering
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