Abstract
Smart health is bringing vast and promising possibilities on the road to comprehensive health management. Smart health applications are strongly data-centric and, thus, empowered by two key factors: information sensing and information learning. In a smart health system, it is crucial to effectively sense individuals’ health information and intelligently learn from its high-level health insights. These two factors are also closely coupled. For example, to enhance the signal quality, a sensing array requires advanced information learning techniques to fuse the information, and to enrich medical insights in mobile health monitoring, we need to combine “multimodal signal processing and machine learning techniques” and “nonintrusive multimodality sensing methods.” In new smart health application exploration, challenges arise in both information sensing and learning, especially their areas of interaction.
Highlights
Smart health is bringing vast and promising possibilities on the road to comprehensive health management
To enhance the signal quality, a sensing array requires advanced information learning techniques to fuse the information, and to enrich medical insights in mobile health monitoring, we need to combine ‘‘multimodal signal processing and machine learning techniques’’ and ‘‘nonintrusive multimodality sensing methods.’’ In new smart health application exploration, challenges arise in both information sensing and learning, especially their areas of interaction
This Special Section in IEEE ACCESS aimed to bring in academic and industrial experts to make their contributions to information sensing and learning in smart health systems
Summary
Smart health is bringing vast and promising possibilities on the road to comprehensive health management. To enhance the signal quality, a sensing array requires advanced information learning techniques to fuse the information, and to enrich medical insights in mobile health monitoring, we need to combine ‘‘multimodal signal processing and machine learning techniques’’ and ‘‘nonintrusive multimodality sensing methods.’’ In new smart health application exploration, challenges arise in both information sensing and learning, especially their areas of interaction. This Special Section in IEEE ACCESS aimed to bring in academic and industrial experts to make their contributions to information sensing and learning in smart health systems. After a rigorous peer-review process, 20 have been accepted for inclusion in the Special Section
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