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Bioengineering
Special Issues
IoT Technology in Bioengineering Applications: Third Edition
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IoT Technology in Bioengineering Applications: Third Edition

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 646

Editors

Dr. Mihaela Hnatiuc

E-Mail Website
Guest Editor
Electronic and Telecommunication Departament, Constanta Maritime University, 104 Mircea cel Batran, 900663 Constanta, Romania
Interests: electronic embedded systems; intelligent sensors and interface; smart home; machine learning; deep learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Larbi Boubchir

E-Mail Website
Guest Editor
LIASD Research Lab, Department of Computer Science, University of Paris 8, 93526 Saint-Denis, France
Interests: biomedical signal processing; EEG; image processing; machine learning; brain–computer interface; biometrics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This is the third volume of the Special Issue "IoT Technology in Bioengineering Applications".

This Special Issue presents novel solutions to challenging real-world problems by applying IoT devices to bioengineering. IoT technology is used in therapies, implants, diagnostics, adaptive prosthetics, etc., where data are recorded and processed in the cloud for Internet-based uses. This method was developed for remote monitoring to improve people's lives. At the same time, eco-plants and biofoods greatly impact human health. IoT technology is used to monitor and diagnose issues with farms and food to improve nutrient content and food quality.

This Special Issue, "IoT Technology in Bioengineering Applications: Third Edition", publishes research using quantitative tools, including simulation and mathematical modeling. It focuses on the exciting applications of bioengineering science in health, medicine, and agronomy.

Dr. Mihaela Hnatiuc
Prof. Dr. Larbi Boubchir
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering 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 2700 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

  • robotic device
  • signal processing
  • image processing
  • communication protocol
  • embedded system
  • smart sensors
  • cloud/FOG
  • predictive methods
  • monitoring
  • process optimization
  • diagnosis
  • implant
  • telesurgery
  • teleconsultation
  • telemonitoring

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Published Papers (1 paper)

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Research

17 pages, 2053 KB  
Article
Agreement and Reliability of a Newly Developed Tidal Volume Monitoring Device in Bag-Valve Ventilation and Intubation Scenarios: A Simulation-Based Study
by Yoonsuk Lee, Eun Young Lee and Hee Young Lee
Bioengineering 2026, 13(8), 930; https://doi.org/10.3390/bioengineering13080930 - 17 Aug 2026
Viewed by 308
Abstract
Background: Manual bag-valve ventilation is a fundamental intervention in prehospital and emergency care but remains highly operator-related and frequently associated with inappropriate tidal volume delivery. Excessive or insufficient ventilation may adversely affect hemodynamics and clinical outcomes. Although real-time tidal volume monitoring has [...] Read more.
Background: Manual bag-valve ventilation is a fundamental intervention in prehospital and emergency care but remains highly operator-related and frequently associated with inappropriate tidal volume delivery. Excessive or insufficient ventilation may adversely affect hemodynamics and clinical outcomes. Although real-time tidal volume monitoring has the potential to improve ventilation quality, its measurement performance across different airway conditions has not been sufficiently evaluated. Methods: This simulation-based repeated-measures study evaluated the measurement agreement and reliability of a newly developed tidal volume monitoring device during manual ventilation using an adult airway management manikin. Twenty emergency medical technicians performed bag-valve ventilation across three airway scenarios: face mask ventilation, endotracheal tube (ETT) intubation, and supraglottic airway (I-gel) insertion. For each scenario, 10 repeated breaths were recorded. Tidal volumes measured by the test device were compared with simulator-derived reference values. Measurement agreement was assessed using paired t-tests, Pearson correlation coefficients, effect sizes, and Bland–Altman analysis, while measurement reliability was evaluated using intraclass correlation coefficients (ICC). Mixed repeated-measures ANOVA was performed to examine interaction effects between airway scenario and operator characteristics. Results: The test device consistently overestimated tidal volume compared with the simulator reference across all airway scenarios (p < 0.001). Correlation between measurements was weak during mask ventilation (r = 0.174) but strong during ETT (r = 0.854) and I-gel (r = 0.709) ventilation, whereas Bland–Altman analysis demonstrated wider limits of agreement in mask ventilation and narrower limits under intubated conditions. ICC analysis revealed airway-dependent reliability, with minimal agreement in normal BVM ventilation but substantially higher agreement during ET-tube and I-gel intubation. Significant effects of airway scenario and operator characteristics (gender, age group, and clinical experience level) were observed, with notable interaction effects between airway scenario and clinical experience. Conclusions: Despite systematic overestimation, the tidal volume monitoring device demonstrated consistent and repeatable performance, particularly under secured airway conditions. Its primary clinical value may lie in reducing operator-related variability and supporting safer manual ventilation through real-time feedback, rather than replacing gold-standard measurement systems. Further algorithm refinement and clinical validation are warranted. Full article
(This article belongs to the Special Issue IoT Technology in Bioengineering Applications: Third Edition)
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