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Special Issue "Smart Sensing Technologies for Personalised Coaching"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: 31 October 2017

Special Issue Editors

Guest Editor
Dr. Oresti Banos

Center for Monitoring and Coaching, University of Twente, Enschede, 7500 AE, Netherlands
Website | E-Mail
Phone: +31(0)53-4895-329
Interests: human-aware computing; behaviour and context modeling; intelligent coaching systems; smart ubiquitous sensing; digital health
Guest Editor
Prof. Dr. Hermie Hermens

Head of Telemedicine Group, Roessingh Research and Development, Enschede, 7500 AH, Netherlands
Website | E-Mail
Phone: +31(0)53-4892-761
Interests: telemedicine; remote monitoring and treatment; smart artificial coaching
Guest Editor
Prof. Dr. Chris Nugent

School of Computing and Mathematics, University of Ulster, Shore Road, Newtownabbey, County Antrim, Northern Ireland, BT37 0QB, UK
Website | E-Mail
Phone: +44-289-0368-330
Interests: pervasive and mobile computing; smart environments, ambient assisted living
Guest Editor
Prof. Dr. Hector Pomares

Research Centre for Information and Communication Technologies, University of Granada, Granada, E-18071, Spain
Website | E-Mail
Phone: +34-95-8241-716
Interests: smart technologies; machine learning; time series prediction; intelligent systems

Special Issue Information

Dear Colleagues,

Lifestyle choices can have a tremendous impact on people’s health and wellness. Avoiding unhealthy habits is, nowadays, a priority, and to achieve this goal, ground-breaking mechanisms are required to automatically and autonomously identify and eventually change people’s behaviours. An increasing number of smart ubiquitous sensing technologies are being developed all over the world to coach people on healthier, as well as more responsible behaviours, providing them timely and ubiquitously with personalised information and support. This Special Issue aims at bringing together the latest experiences, findings and developments on the smart sensing, modelling and understanding of human behaviour for the provision of personalised coaching and support services.

We invite novel, innovative and exciting contributions including sensors used for behavior monitoring and coaching, validity and reliability of sensing modality, and modeling of behavior and coaching strategies. This Special Issue is further interested in:

  • wearable, mobile and ubiquitous health sensing systems,
  • mobile social networks,
  • behavioural grouping and participatory sensing,
  • context-awareness and semantic modelling,
  • physical and virtual coaching systems,
  • benchmarking, datasets and simulation tools that have been applied to study behavior and/or support coaching.

Dr. Oresti Banos
Prof. Dr. Hermie Hermens
Prof. Dr. Christopher Nugen
Prof. Dr. Hector Pomares
Guest Editors

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 monthly 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 1800 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.

Keywords

  • behavior modelling
  • activity recognition
  • emotion recognition
  • location tracking
  • social sensing
  • wearable, mobile and ubiquitous computing
  • intelligent coaching
  • virtual agents

Published Papers (2 papers)

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Research

Open AccessArticle Active2Gether: A Personalized m-Health Intervention to Encourage Physical Activity
Sensors 2017, 17(6), 1436; doi:10.3390/s17061436
Received: 5 May 2017 / Revised: 12 June 2017 / Accepted: 13 June 2017 / Published: 19 June 2017
PDF Full-text (2818 KB) | HTML Full-text | XML Full-text
Abstract
Lack of physical activity is an increasingly important health risk. Modern mobile technology, such as smartphones and digital measurement devices, provides new opportunities to tackle physical inactivity. This paper describes the design of a system that aims to encourage young adults to be
[...] Read more.
Lack of physical activity is an increasingly important health risk. Modern mobile technology, such as smartphones and digital measurement devices, provides new opportunities to tackle physical inactivity. This paper describes the design of a system that aims to encourage young adults to be more physically active. The system monitors the user’s behavior, uses social comparison and provides tailored and personalized feedback based on intelligent reasoning mechanisms. As the name suggests, social processes play an important role in the Active2Gether system. The design choices and functioning of the system are described in detail. Based on the experiences with the development and deployment of the system, a number of lessons learnt are provided and suggestions are proposed for improvements in future developments. Full article
(This article belongs to the Special Issue Smart Sensing Technologies for Personalised Coaching)
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Open AccessArticle Location-Enhanced Activity Recognition in Indoor Environments Using Off the Shelf Smart Watch Technology and BLE Beacons
Sensors 2017, 17(6), 1230; doi:10.3390/s17061230
Received: 2 April 2017 / Revised: 17 May 2017 / Accepted: 19 May 2017 / Published: 27 May 2017
PDF Full-text (2350 KB) | HTML Full-text | XML Full-text
Abstract
Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of
[...] Read more.
Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of body-worn sensors. As this approach suffers with respect to practicality, we propose the use of commercial off-the-shelf devices. In this work, we design and evaluate an activity recognition system composed of a smart watch, which is enhanced with location information coming from Bluetooth Low Energy (BLE) beacons. We evaluate the performance of this approach for a variety of activities performed in an indoor laboratory environment, using four supervised machine learning algorithms. Our experimental results indicate that our location-enhanced activity recognition system is able to reach a classification accuracy ranging from 92% to 100%, while without location information classification accuracy it can drop to as low as 50% in some cases, depending on the window size chosen for data segmentation. Full article
(This article belongs to the Special Issue Smart Sensing Technologies for Personalised Coaching)
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