Special Issue "Data Processing and Wearable Systems for Effective Human Monitoring"
Deadline for manuscript submissions: closed (30 September 2018)
The last few decades have seen an unrestrained development of wearable and mobile technologies, such as smartphones, smartwatches, lightweight sensors, displays, cameras and interfaces for monitoring physiological signs, human behavior, social interaction, cognitive skills, lifestyles, etc.
These devices, that are now equipped with a significant amount of computational power, low-energy wireless communication, long-life battery and large-memory storage, allow novel avenues in the human-centered concept of enlarging the single-user model to a collaborative and distributed network. However, with regard to the current proposal of new miniaturized hardware devices and systems, issues surrounding processing, visualization, and storage of such large amount of available data (including heterogeneous physiological signals) are associated with the challenging discovery of hidden information. In this context, ad-hoc methodologies for data processing and synthesis, as well as ad-hoc experimental paradigms, system design, and models, are strongly needed.
This Special Issue aims at bringing together the significant, cutting-edge research findings in the field of wearable and mobile sensor design and signal processing to manage with data acquisition and processing issues in lab-settings and real ecological scenarios.
Relevant topics may include, but are not limited to, the following:
- Wearable and mobile systems for physiological signal monitoring,
- Wearable and mobile sensor fusion paradigm,
- Embedded signal processing,
- Signal processing of physiological signals in a lab-setting and real-scenarios,
- Collective experience,
- Problem solving,
- Pattern recognition techniques for big heterogeneous physiological data
- Big data analysis,
- Modeling and analysis of data in virtual reality,
- Systems, modeling and analysis of data for e-learning,
- Modeling and analysis of heterogeneous data for personalized health management,
- Data analysis for affective computing,
- Speech acquisition system and data processing,
- Social signal processing.
Dr. Antonio Lanatà
Dr. Alberto Greco
Dr. Nicola Vanello
Manuscript Submission Information
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