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Selected Papers from the 10th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2023)

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 2943

Special Issue Editors


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Guest Editor
Department of Computer Engineering, Automatics and Robotics (ICAR), Information and Communications Technology Centre (CITIC-UGR), University of Granada, 18010 Granada, Spain
Interests: machine learning algorithms; data mining; bioinformatics; computational biology
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Applied Mathematics, University of Granada, 18071 Granada, Spain
Interests: deep learning; statistical analysis in big data; machine learning algorithms; data mining; bioinformatics; computational biology
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical Engineering and Computer Science, Münster University of Applied Sciences, Stegerwaldstraße 39, 48565 Steinfurt, Germany
Interests: embedded/SoC design; ultra low-power design und energy harvesting; circuit architectures for emerging technologies; quantum sensing

Special Issue Information

Dear Colleagues,

The IWBBIO 2023 (10th International Work-Conference on Bioinformatics and Biomedical Engineering) will be held in Gran Canaria, Spain, on 12–14 July 2023. Authors of papers on sensors presented at the conference are invited to submit extended versions of their work to this Special Issue for publication.

IWBBIO 2023 aims to collect high-quality original research papers (including significant work in progress) on any aspect of Bioinformatics, Biomedicine, and Biomedical Engineering.

Authors of conference papers that fall within the scope of Sensors are invited to submit extended papers to this Special Issue. Topics of interest include:

  • Biosensors and data acquisition;
  • Biomedical robotics;
  • Bio-nanotechnology;
  • Biomedical signal/image analysis;
  • Telemedicine;
  • Computer-assisted surgery;
  • Biomarker identification;
  • Image visualization and signal analysis;
  • Disease control and diagnosis;
  • Machine learning in Bioinformatics;
  • Classification for biomedical data;
  • Microarray data analysis;
  • Chip-seq and RNA-Seq analyses;
  • Simulation and visualization of biological systems.

Prof. Dr. Ignacio Rojas
Dr. Francisco Ortuño
Prof. Dr. Olga Valenzuela
Prof. Dr. Peter Gloesekoetter
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 submissions that pass pre-check are 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 2600 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.

Published Papers (3 papers)

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Research

27 pages, 6358 KiB  
Article
Mobile Data Gathering and Preliminary Analysis for the Functional Reach Test
by Luís Francisco, João Duarte, Carlos Albuquerque, Daniel Albuquerque, Ivan Miguel Pires and Paulo Jorge Coelho
Sensors 2024, 24(4), 1301; https://doi.org/10.3390/s24041301 - 17 Feb 2024
Viewed by 726
Abstract
The functional reach test (FRT) is a clinical tool used to evaluate dynamic balance and fall risk in older adults and those with certain neurological diseases. It provides crucial information for developing rehabilitation programs to improve balance and reduce fall risk. This paper [...] Read more.
The functional reach test (FRT) is a clinical tool used to evaluate dynamic balance and fall risk in older adults and those with certain neurological diseases. It provides crucial information for developing rehabilitation programs to improve balance and reduce fall risk. This paper aims to describe a new tool to gather and analyze the data from inertial sensors to allow automation and increased reliability in the future by removing practitioner bias and facilitating the FRT procedure. A new tool for gathering and analyzing data from inertial sensors has been developed to remove practitioner bias and streamline the FRT procedure. The study involved 54 senior citizens using smartphones with sensors to execute FRT. The methods included using a mobile app to gather data, using sensor-fusion algorithms like the Madgwick algorithm to estimate orientation, and attempting to estimate location by twice integrating accelerometer data. However, accurate position estimation was difficult, highlighting the need for more research and development. The study highlights the benefits and drawbacks of automated balance assessment testing with mobile device sensors, highlighting the potential of technology to enhance conventional health evaluations. Full article
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10 pages, 1732 KiB  
Article
Assessment of Directional–Hemispherical Reflectance of Tablets with Cefuroxime during Storage under Elevated Temperature and Ultraviolet Radiation
by Michał Meisner and Beata Sarecka-Hujar
Sensors 2024, 24(2), 630; https://doi.org/10.3390/s24020630 - 19 Jan 2024
Viewed by 494
Abstract
Environmental conditions can lead to changes in the physical and chemical structures of drug products. In this study, the stability of cefuroxime tablets stored under adverse conditions was evaluated based on total directional–hemispherical reflectance (THR). The THR value was measured before and after [...] Read more.
Environmental conditions can lead to changes in the physical and chemical structures of drug products. In this study, the stability of cefuroxime tablets stored under adverse conditions was evaluated based on total directional–hemispherical reflectance (THR). The THR value was measured before and after the tablets’ exposure to stress factors (temperature of 45 °C and UV radiation). Each measurement was performed three times within seven spectral bands at the beginning of the experiment (day 0), and then on days 1, 2, 3, 5, and 7. In addition, hyperspectral profiles (400–1030 nm) were analyzed on days 0 and 7. A significant decrease in THR values in all wavelength ranges was observed when day 7 vs. day 0 were compared, especially for spectral bands of 335–380 nm and 1700–2500 nm (Δ = 0.220, p < 0.001 and Δ = 0.171, p < 0.001, respectively). The hyperspectral analysis confirmed a decrease in the reflectance after the end of stress conditions in the visible light range (400–700 nm) compared to tablets before the experiment. This may indicate that more radiation entered the tablets. In conclusion, the THR of cefuroxime tablets decreases during the exposure to heat and UV radiation, which may result from some physicochemical changes that have occurred during storage. Full article
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19 pages, 6063 KiB  
Article
Fuzzy Controller Implemented for Movement of a Tendon-Driven 3D Robotic Lumbar Spine Mechanism
by Thuanne Paixão, Ana Beatriz Alvarez, Ruben Florez and Facundo Palomino-Quispe
Sensors 2023, 23(24), 9633; https://doi.org/10.3390/s23249633 - 05 Dec 2023
Viewed by 1239
Abstract
Notable efforts have been devoted to the development of biomechanical models of the spine, so the development of a motion system to control the spine becomes expressively relevant. This paper presents a fuzzy controller to manipulate the movement of a 3D robotic mechanism [...] Read more.
Notable efforts have been devoted to the development of biomechanical models of the spine, so the development of a motion system to control the spine becomes expressively relevant. This paper presents a fuzzy controller to manipulate the movement of a 3D robotic mechanism of the lumbar spine, which is driven by tendons. The controller was implemented in Matlab/Simulink R2023a software, MathWorks (Brazil), considering mathematical modeling based on the Lagrangian methodology for simulating the behavior of the lumbar spine dynamic movement. The fuzzy controller was implemented to perform movements of two joints of the 3D robotic mechanism, which consists of five vertebrae grouped into two sets, G1 and G2. The mechanism’s movements are carried out by four servomotors which are driven by readings from two sensors. For control, the linguistic variables of position, velocity and acceleration were used as controller inputs and the torque variables were used for the controller output. The experimental tests were carried out by running the fuzzy controller directly on the 3D physical model (external to the simulation environment) to represent flexion and extension movements analogous to human movements. Full article
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