The aim of the paper is to present a digital retinal imaging hand-held system that consist of few elements - a smartphone and a powerful convex lens, encased together in 3D-printed adapter, allowing acquisition of human retina images. The developed post-processing method allows extracting retina vessels from those images.
The paper presents the construction and the use of a video sensor developed for measuring liquid volume. A characteristic feature of the device is liquid volume measurement carried out based on digital image processing. The paper presents the results of a sensor calibration and measurements taken during the tests. The tests have been specially prepared to use the sensor to control the value of the ventricular assist device stroke volume. It has been shown that the sensor developed by the authors is equipped with a flat, floating membrane that allows measuring the stroke volume in the range of 0 to 80 ml.
The pneumatic type heart assist pump has a pneumatic chamber and a blood chamber separated by a flaccid membrane. By compressing and sucking the gas into the pneumatic chamber, the membrane shape changes as a result the stroke volume will also change. Our task is to determine the real time stroke volume. The idea presented in the work uses shape reconstruction of the membrane created on the basis of image analysis to calculate the stroke volume. This is made possible by equipping the pump with a wide-angle camera and using the DFD method to visually measure the distance between the camera and the characteristic points selected on the surface of the membrane. A new technique was developed based on this for determining the stroke volume of the pneumatic heart assist pump. The work presents a vision sensor for precise control of the pneumatic heart assist pump, as well as results obtained during experimental research.
The heart assist pump of a pneumatic type has a pneumatic chamber and a blood chamber separated by a flaccid membrane. During operation, the membrane changes its shape. Its reconstruction is possible using a camera with a wide-angle lens and the DFD method for visual distance measurement. The measurement is carried out simultaneously at characteristic points indicated by passive markers placed on a membrane surface. Due to their limited number, to obtain a proper numerical description of a membrane shape, spatial interpolation in the actual dimensions is necessary. In the paper, the method of interpolation and the results of reconstruction tests based on 3D printed models were presented.
The work concerns the study of the possibility of using an artificial neural network to determine the ejection volume of pulsatile models of heart assist pumps. The research used new pump designs, significantly different from those used in terms of dimensions and the material from which the flaccid membrane was made. The basis for determining the ejection volume are the special features of the membrane view, which is obtained from the vision sensor. The essence of the method operation depends on associating the membrane view with the corresponding reference volume value, which during the network learning process, is read from the burette with an accuracy of ±0.5 ml. The operation of the artificial neural network consists in the identification of artifacts on the examined views of the membranes and associating them with the ejection volume values. In the case where the membrane view cannot be univocally qualified to the training set, the network acts as an interpolator and predicts the stroke volume value. Verifying the ability to determine the stroke volume by the neural network was performed in close-to-real conditions. In addition to the test results, the article presents new pump designs, the laboratory station and the course of the experiment.
The presented research concerns the determination of the pulse discharge volume of an extracorporeal pneumatic heart assist pump. The publication proposes a method for measuring the discharge volume based on the shape of the surface of the flaccid membrane, which is the pressing element of the pump. The membrane shape was obtained using image processing and analysis methods. The effectiveness of the proposed approach has been experimentally verified and confirmed by the authors. However, firm models of flaccid membranes were used in these studies. This work concerns the verification of the operation of the developed method of measuring the discharge volume in close-to-real conditions. For this purpose, an artificial heart chamber model was used along with a designed and produced measuring system. The article presents the laboratory station, the course of the experiment, obtained results and conclusions.
The publication concerns the reconstruction of the flaccid membrane surface shape based on information in an image obtained from a camera. The article includes results of the research, which aimed at optimizing the position of markers located on the surface of the flaccid membrane. The experiment used a membrane used in a model of an extracorporeal pneumatic heart assist pump. It was expected that the optimization of the position of the markers would increase the accuracy of modeling the shape of the membrane surface. The basis for modeling is the knowledge of the position of markers located in the R3 space. The coordinates of the markers were determined using a visual technique with the help of a camera. Coordinates determined in such a way were subjected to interpolation in three-dimensional space, and then were oversampled. The result is a grid representing the shape of the surface of the flaccid membrane. Evolutionary strategy was used to optimize the position of the markers. For this optimization, a unique design, selection method, a stopping condition method and an assessment function were proposed. The study was carried out for a convex membrane with a known mathematical description. Due to this, it was possible to determine the mapping error of the obtained membrane surface shape in relation to the shape of the reference surface (model), determined from a formula.
The article presents the results of optimizing an illuminator structure, which is an integral part of the optical sensor, for determining the stroke volume and cardiac output of the extracorporeal pulsating heart prosthesis supporting the operation of the myocardium. The obtained results of the optimization were verified experimentally. The tests were carried out for various light sources. The following were taken into account: low and high-current LED diodes operating in the visible band, LED diodes operating in the near-infrared range and fiber optics. In addition to the results of the study, the paper presents problems arising during the use of particular types of illuminators and proposed ways to overcome them.
The article presents the method of encoding a laser beam for control systems. The experiments were performed using a red laser emitting source with a wavelength of λ = 650 nm and a power of P ≈ 3 mW. The aim of the study was to develop methods of modulation and demodulation of the laser beam. Results of research, in which we determined the effect of selected camera parameters, such as image resolution, number of frames per second on the result of demodulation of optical signal, is also shown in the paper. The experiments showed that the adopted coding method provides sufficient information encoded in a single laser beam (36 codes with the effectiveness of decoding at 99.9%).
In the article we presented results obtained during research, which are the continuation of work on the use of artificial neural networks to determine the relationship between the view of the membrane and the stroke volume of the blood chamber of the mechanical prosthetic heart. The purpose of the research was to increase the accuracy of determining the blood chamber volume. Therefore, the study was focused on the technique of the features that the image extraction gives. During research we used the wavelet transform. The achieved results were compared to the results obtained by other previous methods. Tests were conducted on the same mechanical prosthetic heart model used in previous experiments.
In this work we compare two superlattices: InAs/GaSb (sample A) and InAs/InAsSb (sample B). Both samples were grown in MBE VIGO/ MUT laboratory on 2 inch (001) GaAs substrate using MBE technique. We characterized quality and thickness of the samples using three methods: photoluminescence, X-ray diffraction (XRD) and Raman scattering. Period of superlattice layers was obtained using Raman scattering and XRD measurements. For sample A it was equal 5.3 nm and 4.76 nm for InAs and GaSb layers respectively, for sample B 8.3 nm and 9.4 nm. Photoluminescence spectrum for sample A exhibits two peaks: band gap peak at 0.5 eV and deep state peak at 0.25 eV. Spectrum for sample B consists of one band gap peak at 0.17 eV.
In this work we compare two InAs/GaSb superlattice samples grown in MBE VIGO/MUT laboratory on 2 inch (001) GaAs substrate, using MBE technique. Both samples have the same architecture, however their growth processes were conducted at different temperatures. For sample A the growth temperature was equal 668 K (395°C), for sample B 588 K (315°C). Photoluminescence measurements were performed at 30 K. For sample A there is no photoluminescence signal, while spectrum for sample B consists of two peaks: bandgap peak at 0.5 eV and deep state peak at 0.25 eV. X-ray diffraction (XRD) measurements indicate that sample A has better crystallographic quality than sample B. Raman spectra consists of low energy peaks (20-100 cm-1) which confirm the existence of superlattice for both samples [4]. Additionally, for sample A there are peaks related to Sb precipitates. It suggests that except the InAs/GaSb superlattice there is an additional Sb layer which may disturb band structure of superlattice and cause the disappearance of photoluminescence for sample A.
In the paper the research results, which are a continuation of work on the use of image processing techniques to determine the membrane shape of an artificial ventricle, were presented. The studies focused on developing a technique for measuring the accuracy of the membrane shape mapping. It is important to ensure the required accuracy of determining the instantaneous stroke volume of a controlled pneumatic artificial ventricular. Experiments were carried out on the following type of membrane models: convex, flat and concave. The purpose of the research was to obtain a numerical indicator, which will be used to evaluate the options to improve mapping techniques of thee shape of the membrane.
The article presents the construction off a non-contact integrated optical sensor for property protection, with particular emphasis on artwork. The optical sensor described in the paper represents thee programmable and non-contact optical device designed based on a miniature video camera. The video camera used in the sensor was integrated with a high-speed video processing unit. In dangerous situations (during movement of artwork), the sensor generates an alert signal. Object movement is detected based on analysis of variability of a small part of the image of the artwork, which is remembered only inside the sensor during the arming procedure. The described optical sensor determines object movement inn 3D space with the use of a dedicated camera, hardware image processing unit and laser illuminator. The alert signal can be sent to any end point device using Ethernet infrastructures, GSSM or local wireless communication.
The paper presents the use of an artificial neural network in sensors application. The task is to determine the volume of the chamber. The tests were performed on a model of a chamber in a mechanical prosthetic heart. In the considered task the surface of the diaphragm is observed by a near-infrared band camera. The artificial neural network was used to determine the relationship between the real views of the diaphragm and stroke volume. The artificial neural network learning process and research results are presented in the article.
The article presents results achieved during researching the distance measuring method belonging to Depth From Defocus techniques. The method has been developed to determining the shape of the flaccid membrane used in the Ventricular Assist Device (VAD). The shape is determined on the basis of distance measured between the CCD sensor plate of the camera and objects (markers) located on the flaccid membrane. The experiments were carried out using a stationary camera and circular markers with a diameter from 0,003m to 0,009 m. The goal of this paper is to present the influence of the size of the object (marker) on the distance range measured between the camera and diaphragm used in the pneumatic prosthetic heart.
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