Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.4
Journals
Sensors
Special Issues
Biomedical Sensors for Cardiology
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Biomedical Sensors for Cardiology

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

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 6709

Special Issue Editor

Prof. Dr. Omar Escalona

E-Mail Website
Guest Editor
School of Engineering, Jordanstown Campus, Ulster University, Shore Road, Newtownabbey BT37 0QB, UK
Interests: atrial fibrillation surveillance and solutions with improved QALY outcome difference; highly efficient cordless energy supply systems for implanted artificial heart pumps; connected-health enabled cardiovascular healthcare services
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Technologies in cardiovascular healthcare are rapid developing and becoming more sophisticated, increasing the reliability and feasibility of long-term, continuous, and non-invasive monitoring of the heart’s vital signs using a variety of sensor technologies and complex wireless network systems approaches. These include non-standard sensor placements in stable and convenient anatomical locotions on the body’s surface for long-term ECG rhythm monitoring and hemodynamics surrogate measurements from the arm brachial blood vessels by means of dynamic bioimpedance techniques. In addition, therapeutic devices for the treatment of heart diseases could be temporary, leading to a therapies for permanent diseases or destination devices for a particular heart disease. The latter devices are technologically more challenging, as they usually require an implantable device in long-term operation. Nevertheless, they have an increasing demand due to the global aging population. Thus, biomedical sensors development offers a great opportunity to capture dynamic body-surface vital signs of the heart in real-time and in a nonintrusive and continuous mode. Moreover, new biocompatible materials in the development of tissue engineering enable advanced cardiovascular therapeutics destination devices.

   Overall Scope:

  • Wearable biocompatible dry ECG electrodes for long-term monitoring.
  • Wearable armbands for long-term ECG and impedance cardiography (ICG) monitoring methods.
  • Biocompatible materials in tissue engineering and sensors, enabling advanced cardiovascular therapeutics destination devices.

Prof. Dr. Omar Escalona
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 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.

Keywords

  • long-term vital signs monitoring
  • wearable biocompatible dry ECG electrodes
  • body-surface surrogate cardiac contractility monitoring techniques
  • noninvasive sensors
  • cardiovascular therapeutic destination implanted devices
  • tissue engineering solutions in cardiology

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Other

19 pages, 2041 KiB  
Article
FMI-CAECD: Fusing Multi-Input Convolutional Features with Enhanced Channel Attention for Cardiovascular Diseases Prediction
by Tao Lin and Mengyao Fan
Sensors 2024, 24(22), 7160; https://doi.org/10.3390/s24227160 - 7 Nov 2024
Viewed by 724
Abstract
Cardiovascular diseases (CVD) have become a major public health problem affecting the national economy and social development, and have become one of the major causes of death. Therefore, the prevention, control and risk assessment of CVD have been increasingly emphasized. However, current CVD [...] Read more.
Cardiovascular diseases (CVD) have become a major public health problem affecting the national economy and social development, and have become one of the major causes of death. Therefore, the prevention, control and risk assessment of CVD have been increasingly emphasized. However, current CVD prediction models face limitations in capturing complex relationships within physiological data, potentially hindering accurate risk assessment. This study addresses this gap by proposing a novel Framework for Multi-Input, One-dimensional Convolutional Neural Network (1D-CNN) with Attention Mechanism for CVD (FMI-CAECD). This framework leverages the feature extraction capabilities of Convolutional Neural Network (CNN) alongside an Attention Mechanism to adaptively identify critical features and non-linear relationships within the data. Additionally, Shapley Additive Explanations (SHAP) analysis is incorporated to provide deeper insights into individual feature importance for disease prediction. Performance evaluation on the BRFSS 2022 dataset demonstrates that FMI-CAECD achieves superior accuracy (97.45%), sensitivity (96.84%), specificity (95.07%), and F1-score (92.44%) compared to traditional machine learning baselines and other deep learning models. These findings suggest that FMI-CAECD offers a promising approach for CVD risk assessment. Full article
(This article belongs to the Special Issue Biomedical Sensors for Cardiology)
►▼ Show Figures

Figure 1

14 pages, 1867 KiB  
Article
Efficacy of the Cardiac Implantable Electronic Device Multisensory Triage-HF Algorithm in Heart Failure Care: A Real-World Clinical Experience
by Ugur Aslan, Saskia L. M. A. Beeres, Michelle Feijen, Gerlinde M. Mulder, J. Wouter Jukema and Anastasia D. Egorova
Sensors 2024, 24(11), 3664; https://doi.org/10.3390/s24113664 - 5 Jun 2024
Viewed by 1793
Abstract
Heart failure (HF) admissions are burdensome, and the mainstay of prevention is the timely detection of impending fluid retention, creating a window for medical treatment intensification. This study evaluated the accuracy and performance of a Triage-HF-guided carepath in real-world ambulatory HF patients in [...] Read more.
Heart failure (HF) admissions are burdensome, and the mainstay of prevention is the timely detection of impending fluid retention, creating a window for medical treatment intensification. This study evaluated the accuracy and performance of a Triage-HF-guided carepath in real-world ambulatory HF patients in daily clinical practice. In this prospective, observational study, 92 adult HF patients (71 males (78%), with a median age of 69 [IQR 59–75] years) with the Triage-HF algorithm activated in their cardiac implantable electronic devices (CIEDs), were monitored. Following high-risk alerts, an HF nurse contacted patients to identify signs and symptoms of fluid retention. The sensitivity and specificity were 83% and 97%, respectively. The positive predictive value was 89%, and negative predictive value was 94%. The unexplained alert rate was 0.05 alerts/patient year, and the false negative rate was 0.11 alerts/patient year. Ambulatory diuretics were initiated or escalated in 77% of high-risk alert episodes. In 23% (n = 6), admission was ultimately required. The median alert handling time was 2 days. Fifty-eight percent (n = 18) of high-risk alerts were classified as true positives in the first week, followed by 29% in the second–third weeks (n = 9), and 13% (n = 4) in the fourth–sixth weeks. Common sensory triggers included an elevated night ventricular rate (84%), OptiVol (71%), and reduced patient activity (71%). The CIED-based Triage-HF algorithm-driven carepath enables the timely detection of impending fluid retention in a contemporary ambulatory setting, providing an opportunity for clinical action. Full article
(This article belongs to the Special Issue Biomedical Sensors for Cardiology)
►▼ Show Figures

Figure 1

17 pages, 11131 KiB  
Article
A Flexible PDMS-Based Optical Biosensor for Stretch Monitoring in Cardiac Tissue Samples
by Andrea Sannino, Antonio Velarte, Aránzazu Otín, José Ignacio Artigas and Aida Oliván-Viguera
Sensors 2023, 23(23), 9454; https://doi.org/10.3390/s23239454 - 28 Nov 2023
Cited by 1 | Viewed by 1776
Abstract
Cardiotoxicity, characterized by adverse impacts on normal heart function due to drug exposure, is a significant concern due to the potentially serious side effects associated with various pharmaceuticals. It is essential to detect the cardiotoxicity of a drug as early as possible in [...] Read more.
Cardiotoxicity, characterized by adverse impacts on normal heart function due to drug exposure, is a significant concern due to the potentially serious side effects associated with various pharmaceuticals. It is essential to detect the cardiotoxicity of a drug as early as possible in the testing phase of a medical composite. Therefore, there is a pressing need for more reliable in vitro models that accurately mimic the in vivo conditions of cardiac biopsies. In a functional beating heart, cardiac muscle cells are under the effect of static and cyclic stretches. It has been demonstrated that cultured cardiac biopsies can benefit from external mechanical loads that resemble the in vivo condition, increasing the probability of cardiotoxicity detection in the early testing stages. In this work, a biosensor is designed and fabricated to allow for stretch monitoring in biopsies and tissue cultures using an innovative sensing mechanism. The detection setup is based on a biocompatible, thin, flexible membrane—where the samples are attached—which is used as an optical waveguide to detect pressure-caused shape changes and stretches. Various prototypes have been fabricated with a cost-effective process, and different measurements have been carried out to experimentally validate the proposed measurement technique. From these evaluations, stretches of up to 1.5% have been measured, but the performed simulations point towards the possibility of expanding the considered technique up to 10–30% stretches. Full article
(This article belongs to the Special Issue Biomedical Sensors for Cardiology)
►▼ Show Figures

Figure 1

Other

Jump to: Research

15 pages, 4404 KiB  
Case Report
Sensor-Assisted Analysis of Autonomic and Cerebrovascular Dysregulation following Concussion in an Individual with a History of Ten Concussions: A Case Study
by Courtney M. Kennedy, Joel S. Burma and Jonathan D. Smirl
Sensors 2024, 24(13), 4404; https://doi.org/10.3390/s24134404 - 7 Jul 2024
Viewed by 1689
Abstract
Introduction: Concussion is known to cause transient autonomic and cerebrovascular dysregulation that generally recovers; however, few studies have focused on individuals with an extensive concussion history. Method: The case was a 26-year-old male with a history of 10 concussions, diagnosed for bipolar type [...] Read more.
Introduction: Concussion is known to cause transient autonomic and cerebrovascular dysregulation that generally recovers; however, few studies have focused on individuals with an extensive concussion history. Method: The case was a 26-year-old male with a history of 10 concussions, diagnosed for bipolar type II disorder, mild attention-deficit hyperactivity disorder, and a history of migraines/headaches. The case was medicated with Valproic Acid and Escitalopram. Sensor-based baseline data were collected within six months of his injury and on days 1–5, 10, and 14 post-injury. Symptom reporting, heart rate variability (HRV), neurovascular coupling (NVC), and dynamic cerebral autoregulation (dCA) assessments were completed using numerous biomedical devices (i.e., transcranial Doppler ultrasound, 3-lead electrocardiography, finger photoplethysmography). Results: Total symptom and symptom severity scores were higher for the first-week post-injury, with physical and emotional symptoms being the most impacted. The NVC response showed lowered activation in the first three days post-injury, while autonomic (HRV) and autoregulation (dCA) were impaired across all testing visits occurring in the first 14 days following his concussion. Conclusions: Despite symptom resolution, the case demonstrated ongoing autonomic and autoregulatory dysfunction. Larger samples examining individuals with an extensive history of concussion are warranted to understand the chronic physiological changes that occur following cumulative concussions through biosensing devices. Full article
(This article belongs to the Special Issue Biomedical Sensors for Cardiology)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop