Special Issue "Personal Health and Wellbeing Intelligent Systems Based on Wearable and Mobile Technologies"
Deadline for manuscript submissions: closed (20 November 2017)
Prof. Dr. Mario Munoz-Organero
Telematics Engineering Department, University Carlos III de Madrid, Av. Universidad, 30, 28911 Leganes, Madrid, Spain
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Interests: wearable technologies for health and wellbeing applications; mobile and pervasive computing for assistive living; Internet of Things and assistive technologies; machine learning algorithms for physiological; inertial and location sensors; personal assistants and coaching for health self-management; activity detection and prediction methods
Wearable and mobile personal devices are becoming more ubiquitous, from smart phones, bands, glasses and watches to smart clothes and implants. These wearable sensing technologies can provide 24/7 physiological and movement data that enhance the knowledge base for the user or groups of users. They constitute the internal fabric of an Internet of Smart Things that provides the basis to better understand the user, what the user does, when, how and even why. Both physical and mental health related information can be extracted or inferred from the diverse nature of the data. This Special Issue aims to publish up-to-date research in developing personal applications, methods and algorithms based on information extracted or inferred from wearable and mobile sensor devices. This wealth of information facilitates users to better self-manage their health and wellbeing. Both theoretical models to process sensor data, proof of concept and user ready applications are welcome.
Some of the topics of interest for this Special Issue include:
- Data gathering from users and patients based on wearable technology and sensor devices
- Feature extraction from wearable sensors
- Probabilistic models and inference
- Machine learning techniques applied to wearable sensor data.
- Multi-sensor data fusion
- Learning from wearable data
- Optimization techniques and model training based on wearable sensor data
- Health and wellbeing models based on wearable sensor data
- Personal recommender systems for self-management for long term conditions
- Personal recommender systems for self-management in rehabilitation
- User interfaces and personalized feedback
- User experiments
- User applications
- Novel wearable sensor devices
- Big data in health from wearable devices
- Privacy, security and ethical aspects
- Adoption of wearable sensors by the national health systems in Europe
- Future trends
- Regulations in different countries
Prof. Dr. Mario Munoz-Organero
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. Technologies is an international peer-reviewed open access quarterly 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 350 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.
- Wearable sensors
- Mobile devices and applications
- Personal health and wellbeing
- Intelligent systems and machine learning algorithms
- Internet of things