Electromagnetic Fields in Bioengineering: Advancing the OneHealth Paradigm

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

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1423

Special Issue Editors


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Guest Editor
Institute of Electronics Computer and Telecommunication Engineering (IEIIT), National Research Council (CNR), Milan, Italy
Interests: bioengineering; interaction of EMF with biological system; bioelectromagnetism; computational methods; stochastic and ML tools; computational neuroscience; magnetoelectric nanomaterials modeling
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Electronics Computer and Telecommunication Engineering (IEIIT), National Research Council (CNR), Milan, Italy
Interests: bioengineering; interaction of EMF with biological system; bioelectromagnetism; computational methods; stochastic and ML tools; wearable device; RF and mm-waves technologies
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Electronics, Information Engineering and Telecommunications (IEIIT), National Research Council of Italy (CNR), 20133 Milan, Italy
Interests: computational modeling and characterization of innovative techniques based on EMF for medical applications; bioelectromagnetism; EMF-based neurostimulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The application of electromagnetic fields (EMFs) in biomedicine has experienced remarkable growth in recent years, significantly improving patient quality of life. From diagnostic technologies to innovative therapeutic approaches, EMFs have demonstrated notable potential for addressing complex medical challenges with non-invasive or minimally invasive applications and for the exchange of sensitive health data through wireless RF and mm wave technologies.

Within this context, the OneHealth approach emerges as a fundamental paradigm, recognizing that human health is intrinsically connected to environmental and ecological factors. Electromagnetic field applications, viewed through the OneHealth lens, offer unique opportunities to develop solutions that benefit multiple aspects of health, leading to more comprehensive medical and public health approaches.

In parallel, recent advancements in computational modeling and novel stochastic and machine learning tools have opened new frontiers for the study of EMF–biological system interactions and secure sensitive data transmission. As these technologies continue to evolve, there is an urgent need to explore their full potential while addressing safety concerns and standardization issues.

We are pleased to invite you to submit your work to this Special Issue on "Electromagnetic Fields in Bioengineering: Advancing the OneHealth Paradigm", which will focus on cutting-edge research and developments in this rapidly evolving field.

Both original research contributions and review papers are welcome, which may include, but are not limited to, the following topics:

  • Innovative computational modeling and simulation of EMF interactions with biological tissues.
  • Novel therapeutic applications of EMFs (e.g., cancer treatment, regenerative medicine, and neurostimulation).
  • Advanced diagnostic techniques utilizing electromagnetic technologies.
  • Innovative materials and devices for EMF generation and detection in medical applications.
  • Wireless technologies for healthcare monitoring and telemedicine.
  • Safety considerations and biological effects of EMF exposure.
  • Machine learning and AI approaches for EMF-based diagnostics and therapies.
  • Environmental monitoring through electromagnetic field-based technologies.
  • Integrated OneHealth approaches for EMF technologies in health surveillance.

We look forward to your valuable contributions.

Dr. Marta Bonato
Dr. Silvia Gallucci
Dr. Emma Chiaramello
Guest Editors

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Keywords

  • biological tissue-EMF interactions
  • bioelectromagnetism
  • OneHealth
  • environmental health
  • therapeutic and diagnostic EMF applications
  • EMF safety in medicine
  • RF/mm-wave medical technologies

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Published Papers (2 papers)

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Research

13 pages, 2523 KB  
Article
Body Size Modulates the Impact of the Dispersive Patch Position During Radiofrequency Cardiac Ablation
by Ramiro M. Irastorza and Enrique Berjano
Bioengineering 2025, 12(10), 1017; https://doi.org/10.3390/bioengineering12101017 - 24 Sep 2025
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Abstract
(1) Background: In the context of cardiac radiofrequency (RF) ablation, it has been proposed that positioning the dispersive patch (DP) concordantly with the orientation of the ablation electrode may enhance lesion size. The objective of this study is to investigate how individual body [...] Read more.
(1) Background: In the context of cardiac radiofrequency (RF) ablation, it has been proposed that positioning the dispersive patch (DP) concordantly with the orientation of the ablation electrode may enhance lesion size. The objective of this study is to investigate how individual body size may modulate the extent of this effect. (2) Methods: Three computational models representing different body sizes were developed. An irrigated catheter ablation was simulated by delivering a 30 W pulse for 30 s to the endocardial surface of the anterior wall. Lesion sizes were then compared between two configurations of the dispersive patch (DP): an anterior (concordant) position and a posterior (discordant) position. (3) Results: Lesion size was consistently and significantly greater with concordant DP positioning compared to discordant positioning. Moreover, the magnitude of this difference decreased significantly with increasing body size, ranging from 0.65 ± 0.08 mm in the 35 kg swine model to 0.51 ± 0.06 mm in the human model. (4) Conclusions: Body size has a modest influence on the effect of dispersive patch positioning on RF lesion size. The potential advantage of a concordant DP configuration may be more significant in individuals with smaller body volume. Full article
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16 pages, 1628 KB  
Article
Anatomical Characteristics Predict Response to Transcranial Direct Current Stimulation (tDCS): Development of a Computational Pipeline for Optimizing tDCS Protocols
by Giulia Caiani, Emma Chiaramello, Marta Parazzini, Eleonora Arrigoni, Leonor J. Romero Lauro, Alberto Pisoni and Serena Fiocchi
Bioengineering 2025, 12(6), 656; https://doi.org/10.3390/bioengineering12060656 - 15 Jun 2025
Viewed by 915
Abstract
Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique promisingly used to treat neurological and psychological disorders. Nevertheless, the inter-subject heterogeneity in its after-effects frequently limits its efficacy. This can be attributed to fixed-dose methods, which do not consider inter-subject anatomical [...] Read more.
Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique promisingly used to treat neurological and psychological disorders. Nevertheless, the inter-subject heterogeneity in its after-effects frequently limits its efficacy. This can be attributed to fixed-dose methods, which do not consider inter-subject anatomical variations. This work attempts to overcome this constraint by examining the effects of age and anatomical features, including the volume of cerebrospinal fluid (CSF), the thickness of the skull, and the composition of brain tissue, on electric field distribution and cortical excitability. A computational approach was used to map the electric field distribution over the brain tissues of realistic head models reconstructed from MRI images of twenty-three subjects, including adults and children of both genders. Significant negative correlations (p < 0.05) were found in the data between the maximum electric field strength and anatomical variable parameters. Furthermore, this study showed that the percentage of brain tissue exposed to an electric field amplitude above a pre-defined threshold (i.e., 0.227 V/m) was the main factor influencing the responsiveness to tDCS. In the end, the research suggests multiple regression models as useful tool to predict subjects’ responsiveness and to support a personalized approach that tailors the injected current to the morphology of the patient. Full article
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