ABSTRACT
Objective Taking pig kidney as an example, through a series of comparative and analogical experiments, the influencing factors of compressive stress at relaxation stage of biological tissues were analyzed, and a more accurate and widely applicable biomechanical model at relaxation stage was established. Methods The compressive stress relaxation experiments of pig kidney under different conditions were carried out by using the self-built mechanical experiment platform. The collected data were analyzed and mapped, and various factors affecting the relaxation force changes were summarized. Based on the conclusion, the neural network learning algorithm was used to model the force change process at relaxation stage of pig kidney. Results The pre-extrusion pressure and relaxation time were the main influencing factors for compressive stress changes of biological tissues at relaxation stage. The average error of test sample validation experiment was 6.4 mN, and the average prediction error of generalization sample validation experiment was 34.9 mN, so the modeling effect was good. Conclusions Neural network modeling algorithm has the advantages of strong generalization ability and good fault tolerance, which contributes to providing more realistic force tactile feedback prediction for virtual surgery system. It is also a new idea for mechanical modeling of nonlinear biological tissues.
ABSTRACT
The prevalence of cardiovascular disease in our country is increasing, and it has been a big problem affecting the social and economic development. It has been demonstrated that early intervention of cardiovascular risk factors can effectively reduce cardiovascular disease-caused mortality. Therefore, extensive implementation of cardiovascular testing and risk factor screening in the general population is the key to the prevention and treatment of cardiovascular disease. However, the categories of devices available for quick cardiovascular testing are limited, and in particular, many existing devices suffer from various technical problems, such as complex operation, unclear working principle, or large inter-individual variability in measurement accuracy, which lead to an overall low popularity and reliability of cardiovascular testing. In this study, we introduce the non-invasive measurement mechanisms and relevant technical progresses for several typical cardiovascular indices (e.g., peripheral/central arterial blood pressure, and arterial stiffness), with emphasis on describing the applications of biomechanical modeling and simulation in mechanism verification, analysis of influential factors, and technical improvement/innovation.
Subject(s)
Humans , Arterial Pressure , Biomechanical Phenomena , Blood Pressure , Blood Pressure Determination , Reproducibility of Results , Risk FactorsABSTRACT
Objective To study the process of stent graft implantation into the aortic dissection model by finite element simulation, calculate the stress distribution at different locations of the aorta after the implantation, and analyze the biomechanical mechanism of new lesions for implantation of stent grafts. Methods Based on the computed tomography angiography (CTA) image data of the aorta, a three-dimensional geometric model of patient-specific aortic dissection was established with image segmentation and reconstruction. The wall thickness and material properties of the aortic dissection of the computational models were set according to the literature data. Stent grafting rings with different geometric parameters were designed in a computer-aided design (CAD) software, and the procedure of stent graft implantation was simulated by a finite element analysis software. Results When the implanted stent graft reached a steady-state, the maximum Von Mises stress of the aorta was markedly related to the position of the stent graft and located at the bare stent or small nickel-titanium alloy ring. In the long-term, this force might cause a new tear to appear at the treated aorta. Conclusions The position of the stent graft had a weak effect on the distribution of the maximum Von Mises stress of the aorta, but there was an obvious effect on the Von Mises stress of the aorta. These research outcomes may provide significant guidance for selecting the position of the stent graft.
ABSTRACT
Resumen En este artículo se describe detalladamente el proceso de captura de una actividad de neurorehabilitación en miembros superiores dispuesta en rutina clínica, utilizando dispositivos que permiten extraer variables de interés clínico, dentro de las cuales se encuentra el tiempo, la movilidad y ángulos. Estas variables se almacenarán cuantitativamente, de manera que sea posible tener un seguimiento continuo y exhaustivo sobre la rehabilitación del paciente, y así tener verosimilitud de cumplimiento en estas rutinas.
Abstract This article describes, in detail, the process of capturing a neuro-rehabilitation activity in upper limbs for clinical routines, using devices that enable the extraction of variables of clinical interest within the patient's task of execution, within which there is a focus on time, mobility and angles. These variables will be stored quantitatively, so that it is possible to have continuous and exhaustive follow-ups of the rehabilitation of the patient and, thus having compliance authenticity in these routines.
Resumo Neste artigo descreve-se detalhadamente o processo de captura de uma atividade de neuroreabilitação em membros superiores disposta em rotina clínica, utilizando dispositivos que permitem extrair variáveis de interesse clínico, dentro das quais se encontra o tempo, a mobilidade e ângulos. Estas variáveis se armazenaram quantitativamente, de maneira que seja possível ter um rastreamento contínuo e exaustivo sobre a reabilitação do paciente, e assim ter verossimilitude de cumprimento nestas rotinas.