Special Issue "Data Analytics and Applications of Wearable Sensors in E-health"
Deadline for manuscript submissions: 30 August 2020.
Interests: e-Health; personalized health; data semantics; data stream processing; e-Health ontologies; stream processing agents
Recent developments in sensing technologies and wearables are changing the way personal data are acquired and generated, opening the doors for novel paradigms in data analytics. Ranging from motion detection to non-invasive observation of physiological parameters, they have the potential to be used in a large number of use-cases and applications, especially in the healthcare domain. Considering the advantages of counting with real-time observations and having wearables used in everyday life, healthcare professionals have the opportunity to observe and analyze patient behaviors, compliance to therapy, exercise assessment, emotional status, evolution of a health condition, etc. The benefits of having access to these data are reflected in the numerous e-Health applications and prototypes developed in several subdomains. Nevertheless, using solely the data acquired through these devices is often not enough to address these challenges effectively. Data science, AI, and in particular machine learning approaches are required to first preprocess, harmonize, and distil the data, and then to derive knowledge and insights that can be translated into actionable elements for patients, physicians and other healthcare professionals.
This Special Issue focuses on the application of data science and analytics techniques in e-Health, considering the combination of wearable sensing devices and IoT technologies as primary data sources. Contributions are expected to cover a large range of application domains, from monitoring of chronic diseases, virtual coaching for the aging population, exercise and rehabilitation assessment, to general wellbeing and other applications related to health. Contributions may also consider the exploration of novel wearable technologies in the biomedicine domain, nanotechnologies, e-textiles, etc. Submissions may also focus on different aspects of data analytics of sensor data for e-Health, including but not limited to novel methods for semantic data analysis, data streaming, real-time processing, computational persuasion and personalization, machine learning and explainability, distributed IoT infrastructures, and agent and agreement technologies.
Dr. Jean-Paul Calbimonte
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- e-Health data analytics for wearables
- e-Health wearable sensors
- e-Health ontologies for sensing data
- Semantic e-Health data analysis
- Data stream processing for sensor data
- Real-time processing and constraints
- e-Health image processing for wearables
- e-Health signal processing for wearables
- Computational persuasion for IoT and wearables
- Personalized e-Health applications
- Machine learning and explainability for e-Health
- e-Health multi-agent systems
- e-Health cloud/fog/edge infrastructures & analytics
- Virtual coaching using wearable sensors
- e-Health and data analytics applications and use-cases