Data Analytics for Mobile-Health
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 19111
Special Issue Editors
Interests: machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: explainable AI; machine learning; knowledge base system
Special Issue Information
Dear Colleagues,
Mobile health represents a promising horizon to promote the continuous and proactive monitoring of healthcare. The increasing development and commercial availability of wearables and low-cost portable devices is rapidly opening up new perspectives and opportunities for daily self-management of our own health and wellbeing. Mobile health and remote health are key technologies to promote public health (people can be assisted by clinical personnel remotely, without the need to regularly go to the hospital) and to relieve the costs associated to national healthcare.
At the same time, the development of mobile health solutions, including wearables and low-cost off-of-the-shelf biometric devices, have also raised previously unseen challenges: (a) the design of efficient data analytics based on limited setups with poor signal quality (compared to research-grade or clinical-purpose devices); (b) their lightweight implementation in a mobile-health framework; (c) the need for a human-understandable interpretation or explanation behind complex reasoning artificial intelligence-based data analytics; (d) the need for user-friendly and highly usable data visualization tools to increase the empowerment of the final users in managing their own health and wellbeing.
In this Special Issue, we invite original research papers and review articles aimed at promoting novel data analytics methods for mobile health solutions, methods for sensor fusion and data fusion and investigations about the explainability of available data analytics for mobile health, as well as on field experiences of mobile health applications.
Topics:
- mobile health;
- remote health;
- in-home monitoring;
- e-health;
- wearables and body area networks;
- smart biosensors;
- low-cost sensors;
- self-diagnosis;
- data fusion;
- sensor fusion;
- deep learning;
- machine learning;
- artificial intelligence;
- data analytics.
Dr. Italo Zoppis
Dr. Sara Lucia Manzoni
Dr. Giulia Cisotto
Guest Editors
Manuscript Submission Information
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Keywords
- deep learning
- machine learning
- mobile-health
- wearables
- smart sensors
- human data, self-diagnosis
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