Advanced Assessment of Medical Devices

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 554

Special Issue Editors


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Guest Editor
School of Engineering, University of Birmingham, Birmingham, UK
Interests: tribology; corrosion; total joint replacement; biomaterials

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Guest Editor
School of Engineering, University of Birmingham, Birmingham, UK
Interests: tribology; corrosion; material characterisation; mechanical properties

E-Mail Website
Guest Editor
School of Engineering, University of Birmingham, Birmingham, UK
Interests: spinal technology and assessment; joint arthroplasty; bone disease and trauma; medical device technology

Special Issue Information

Dear Colleagues,

The preclinical assessment of implantable medical devices is essential for enhancing both their safety and efficacy before reaching the patient. In light of recent high-profile clinical failures, preclinical testing regimes which previously used simplified or averaged conditions and ex situ analysis have faced increased scrutiny. This fails to capture clinically relevant failure modes and provides limited actionable or predictive data on the long-term performance of devices, hindering the effective translation and adoption of emerging technologies. An increase in the popularity of and demand for implants in younger patients, or those with complex healthcare needs, means that current preclinical testing domains are not representative. Furthermore, new and disruptive technologies often necessitate the need for advanced testing. This burgeoning calls for in silico models that drive innovation, offering great potential to address the growing and varied challenges in medical device development, but this is challenged by appropriate experimentally derived inputs and verification/validation frameworks.

This Special Issue of Bioengineering on Advanced Assessment of Medical Devices aims to showcase device development and assessment that goes beyond the current state of the art by inviting contributions from the community in the following areas (among others):

  • Advanced preclinical testing;
  • Device–biology interaction;
  • Co-creation with patients, clinicians, regulators, and industrial partners;
  • Machine learning and in silico digital twin methodologies;
  • Predictive models for device behaviour in vitro and in vivo;
  • High-throughput methodologies for biomaterial characterisation;
  • Regulatory science.

Dr. Andrew Robert Beadling
Prof. Dr. Michael Bryant
Prof. Dr. Richard M. Hall
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. 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

  • medical devices
  • preclinical assessment
  • biomaterials
  • bioengineering
  • regulatory science
  • digital twins

Published Papers (1 paper)

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Research

14 pages, 3920 KiB  
Article
Verification and Validation of Advanced Control Systems for a Spinal Joint Wear Simulator
by Kaushikk Ravender Iyer, David Keeling and Richard M. Hall
Bioengineering 2024, 11(8), 779; https://doi.org/10.3390/bioengineering11080779 - 1 Aug 2024
Viewed by 310
Abstract
Wear simulation aims to assess wear rates and their dependence on factors like load, kinematics, temperature, and implant orientation. Despite its significance, there is a notable gap in research concerning advancements in simulator control systems and the testing of clinically relevant waveforms. This [...] Read more.
Wear simulation aims to assess wear rates and their dependence on factors like load, kinematics, temperature, and implant orientation. Despite its significance, there is a notable gap in research concerning advancements in simulator control systems and the testing of clinically relevant waveforms. This study addresses this gap by focusing on enhancing the conventional proportional–integral–derivative (PID) controller used in joint simulators through the development of a fuzzy logic-based controller. Leveraging a single-input multiple-output (SIMO) fuzzy logic control system, this study aimed to improve displacement control, augmenting the traditional proportional–integral (PI) tuning approach. The implementation and evaluation of a novel Fuzzy-PI control algorithm were conducted on the Leeds spine wear simulator. This study also included the testing of dailyliving (DL) profiles, particularly from the hip joint, to broaden the scope of simulation scenarios. While both the conventional PI controller and the Fuzzy-PI controller met ISO tolerance criteria for the spine flexion–extension (FE) profile at 1 Hz, the Fuzzy-PI controller demonstrated superior performance at higher frequencies and with DL profiles due to its real-time adaptive tuning capability. The Fuzzy-PI controller represents a significant advancement in joint wear simulation, offering improved control functionalities and more accurate emulation of real-world physiological dynamics. Full article
(This article belongs to the Special Issue Advanced Assessment of Medical Devices)
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