Special Issue "Selected Papers from ICBRA 2017"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (10 March 2018)

Special Issue Editor

Guest Editor
Prof. Ralf Hofestädt

Bioinformatics Department, Bielefeld University, Bielefeld, Germany
Website | E-Mail
Interests: biomedical data management; modeling and simulation of metabolic processes; parallel computing and multimedia implementation of virtual scenarios

Special Issue Information

Dear Colleagues,

The 2017 International Conference on Bioinformatics Research and Applications (ICBRA 2017) will be held in Barcelona, Spain, 8–10 December, 2017. ICBRA 2017 is aimed at keeping abreast of the current development and innovation in advanced research areas of “Bioinformatics Research and Applications”, as well as providing an engaging forum for participants to share knowledge and expertise on related issues. The ICBRA series will be held annually to include innovative academics and industrial experts. This Special Issue intends to contain a selection of carefully-revised and extended best papers, to be presented at ICBRA 2017. Paper acceptance for ICBRA 2017 will be based on quality, relevance to the conference theme and originality.

The authors of a number of selected full papers of high quality will be invited after the conference to submit revised and extended versions of their originally-accepted conference papers to this Special Issue of Information, published by MDPI, in open access. The selection of these best papers will be based on their ratings in the conference review process, quality of presentation during the conference, and expected impact on the research community. Each submission to this Special Issue should contain at least 50% of new material, e.g., in the form of technical extensions, more in-depth evaluations, or additional use cases. These extended submissions will undergo a peer-review process according to the journal’s rules of action. At least two technical committees will act as reviewers for each extended article submitted to this Special Issue; if needed, additional external reviewers will be invited to guarantee a high-quality reviewing process.

Prof. Ralf Hofestädt
Guest Editor

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. Information 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 850 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

  • Bio-Data Mining
  • Bio-Visualization
  • Biomedical Signal and Image Analysis
  • Computational Modeling and Data Integration
  • Machine Learning
  • Healthcare Information Systems

Published Papers (2 papers)

View options order results:
result details:
Displaying articles 1-2
Export citation of selected articles as:

Research

Open AccessArticle Definition of Motion and Biophysical Indicators for Home-Based Rehabilitation through Serious Games
Information 2018, 9(5), 105; https://doi.org/10.3390/info9050105
Received: 10 March 2018 / Revised: 23 April 2018 / Accepted: 26 April 2018 / Published: 1 May 2018
PDF Full-text (3112 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we describe Remote Monitoring Validation Engineering System (ReMoVES), a newly-developed platform for motion rehabilitation through serious games and biophysical sensors. The main features of the system are highlighted as follows: motion tracking capabilities through Microsoft Kinect V2 and Leap Motion
[...] Read more.
In this paper, we describe Remote Monitoring Validation Engineering System (ReMoVES), a newly-developed platform for motion rehabilitation through serious games and biophysical sensors. The main features of the system are highlighted as follows: motion tracking capabilities through Microsoft Kinect V2 and Leap Motion are disclosed and compared with other solutions; the emotional state of the patient is evaluated with heart rate measurements and electrodermal activity monitored by Microsoft Band 2 during the execution of the functional exercises planned by the therapist. The ReMoVES platform is conceived for home-based rehabilitation after the hospitalisation period, and the system will deploy machine learning techniques to provide an automated evaluation of the patient performance during the training. The algorithms should deliver effective reports to the therapist about the training performance while the patient exercises on their own. The game features that will be described in this manuscript represent the input for the training set, while the feedback provided by the therapist is the output. To face this supervised learning problem, we are describing the most significant features to be used as key indicators of the patient’s performance along with the evaluation of their accuracy in discriminating between good or bad patient actions. Full article
(This article belongs to the Special Issue Selected Papers from ICBRA 2017)
Figures

Figure 1

Open AccessArticle Robust Eye Blink Detection Based on Eye Landmarks and Savitzky–Golay Filtering
Information 2018, 9(4), 93; https://doi.org/10.3390/info9040093
Received: 11 March 2018 / Revised: 29 March 2018 / Accepted: 9 April 2018 / Published: 15 April 2018
PDF Full-text (516 KB) | HTML Full-text | XML Full-text
Abstract
A new technique to detect eye blinks is proposed based on automatic tracking of facial landmarks to localise the eyes and eyelid contours. Automatic facial landmarks detectors are trained on an in-the-wild dataset and shows an outstanding robustness to varying lighting conditions, facial
[...] Read more.
A new technique to detect eye blinks is proposed based on automatic tracking of facial landmarks to localise the eyes and eyelid contours. Automatic facial landmarks detectors are trained on an in-the-wild dataset and shows an outstanding robustness to varying lighting conditions, facial expressions, and head orientation. The proposed technique estimates the facial landmark positions and extracts the vertical distance between eyelids for each video frame. Next, a Savitzky–Golay (SG) filter is employed to smooth the obtained signal while keeping the peak information to detect eye blinks. Finally, eye blinks are detected as sharp peaks and a finite state machine is used to check for false blink and true blink cases based on their duration. The efficiency of the proposed technique is shown to outperform the state-of-the-art methods on three standard datasets. Full article
(This article belongs to the Special Issue Selected Papers from ICBRA 2017)
Figures

Figure 1

Back to Top