Analysis and modeling of forced-damped vibrations and their applications in medicine-ZENTIME PUBLISHING CORPORATION LIMITED

Home Progress in Medical Devices All issues Issue 1

Analysis and modeling of forced-damped vibrations and their applications in medicine

Zine Ghemari

Electrical Engineering Department, Mohamed Boudiaf University of M’sila, 28000, Algeria

Address correspondence to: Zine Ghemari, Electrical Engineering Department, Mohamed Boudiaf University of M’sila, P.O. Box 166, Ichbilya, M’Sila 28000, Algeria. E-mail: ghemari-zine@live.fr.

DOI: https://doi.org/10.61189/871955jstyqr

Received December 20, 2023; Accepted February 27, 2024; Published March 31, 2024

Highlights

● The study explores how forced-damped vibrations can be applied in various medical contexts. This may include using vibrations for medical imaging techniques such as ultrasound or MRI, where vibrations are applied to the body to generate images of internal structures.

● Vibrations can also be utilized for tissue characterization, diagnosis of medical conditions, and therapeutic interventions such as vibration therapy for rehabilitation or pain management.

Abstract

Forced-damped vibrations are pivotal in various medical applications, significantly contributing to the examination of tissue mechanical properties, development of medical devices, and understanding of biological systems’ complexities. These vibrations represent the dynamic behavior of systems subjected to external forces and damping, where an external force continues to act, and damping determines the rate of energy dissipation. Advanced exploration of damping properties has led to the creation of novel technologies and methods, enhancing our ability to probe and manipulate the complex mechanical dynamics of biological tissues.

Keywords: Analysis, modeling, damped vibrations, medicine

Download

Cite

Views

2330

Downloads

Lastest Issue

Construction and comparative analysis of an early screening prediction model for fatty liver in elderly patients based on machine learning Analysis of urinary non-formed components at home based on machine learning algorithms Integrating Traditional Chinese Medicine massage therapy with machine learning: A new trend in future healthcare Optimization design and performance study of magnesium alloy vascular clamp Review of methods for detecting electrode-tissue contact status during atrial fibrillation ablation Research progress and clinical application of cooled radiofrequency ablation Applications of vibration sensors in medicine: Enhancing healthcare through innovative monitoring Advancements in irreversible electroporation ablation technology for treating atrial fibrillation Research progress of photoacoustic imaging technology in brain diseases