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Long-Term Health Monitoring with Physiological Signals

Topic Information

Dear Colleagues,

The human body constantly gives out physiological signals, such as heat, electrical impulses from muscles, brain, and other organs. Since the dawn of modern medicine, these signals have been used to assess and, in some cases, determine the cause of health crisis. From these ancient roots, modern medicine has grown and diversified. However, the idea of crisis is still preserved. Like Hippocrates of Kos, modern medicine springs into action when a health crisis occurs. This event-driven setup is very resource efficient because health services are only used if there is reason to do so. However, sometimes a disease might have progressed beyond a point where effective treatment is available before symptoms trigger a diagnosis. In the past, resource efficiency by far outweighed the potential benefits of continuous physiological signal monitoring. However, in recent years, technological advances have meant that communication, storage, and processing resources have become almost omnipresent at a competitive price point. Having recognized the transformative nature of this technology, for this topic, entitled “Long-Term Health Monitoring with Physiological Signals”, we seek answers to the question: How can we use physiological signal measurements to translate the resource abundance into improved outcomes for patients? We invite papers that recognize the potential of gathering and analysing big physiological data for possible publication in one of the three journals: Diagnostics, International Journal of Environmental Research and Public Health, or Signals. A possible application area is the creation of disease-specific solutions where physiological signals are analysed with advanced artificial intelligence algorithms. Examples include atrial fibrillation detection and sleep monitoring in the home environment. Another area of interest is long-term physiological signal analysis for rehabilitation tracking and geriatric care.

Dr. Oliver Faust
Prof. Dr. U Rajendra Acharya
Topic Editors

Keywords

  • physiological signals
  • internet of medical things
  • mobile health
  • long term monitoring
  • artificial intelligence
  • hybrid medical decision support
  • rehabilitation
  • geriatric care

Participating Journals

Diagnostics
Open Access
17,197 Articles
Launched in 2011
3.3Impact Factor
5.9CiteScore
21 DaysMedian Time to First Decision
Q1Highest JCR Category Ranking
International Journal of Environmental Research and Public Health
Open Access
65,466 Articles
Launched in 2004
-Impact Factor
8.5CiteScore
28 DaysMedian Time to First Decision
-Highest JCR Category Ranking
Signals
Open Access
287 Articles
Launched in 2020
2.6Impact Factor
4.6CiteScore
23 DaysMedian Time to First Decision
Q2Highest JCR Category Ranking

Published Papers