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.
Tapered optical fibers are created by stretching of the optical fiber so that their diameter at the narrowest area is only few
microns. In this form, they are very interesting for optical sensor applications. The developed vision sensor for a filament
positioning is a key element of the optical fiber tapering system. It allows controlling the speed of stretching the fiber
what significantly reduces the chance of its breaking. The paper presents the sensor developed based on a fixed-focus
camera equipped with a wide-angle lens and using image processing and analysis techniques. Determining the position
of a filament consists in determining the angle of its deviation from the reference position. The required stretching speed
of the fiber is determined based on the determined angle. In the paper, the way of carrying out measurements of position
of optical fiber using the sensor and the results obtained were presented.
The Depth from Defocus (DFD) type method was developed for visual distance measurement. It was used to determine the shape of the flaccid membrane of the extracorporeal pneumatic heart assist pump. In the previous conference paper the technique of accuracy measurement of membrane shape mapping of an artificial ventricle was presented. The study was conducted on three membrane shapes which are well mathematically described: convex, concave and flat. For all cases the rigid membrane models were designed and 3D printed. The next study focused on extending the invented technique to other models of membrane with the well-known math formulas. Two new irregularly shaped models were produced and tested. Analysis of the obtained results during the rigid membrane models tests revealed the significant effect of the markers arrangement on the membrane shape mapping accuracy. Therefore, another arrangement of markers was tested. In the paper the comparison of the results obtained for the different arrangements of markers was presented.
The new visual method has been invented in order to measure the stroke volume of the extracorporeal pneumatic heart assist pump. Heart pumps of this type have a pneumatic chamber and a blood chamber separated by a flaccid membrane. Equipping the heart pump with a miniature camera makes it possible to observe the surface of the membrane from the pneumatic chamber side without obstructing its normal operation. The momentary shape of the flaccid membrane affects the volume of the blood chamber. The essence of the used measurement method is to observe a surface of the membrane using a camera and to determine the shape of this membrane in the actual 3-dimensional space, only on the basis of a one-shot image. This method works due to markers arranged on the surface of the membrane from the pneumatic chamber side. In the measurement, the image processing and analysis techniques are used. The difficulty of the accuracy verification of the shape mapping is that heart assist pump fitted with a flaccid membrane has only two membrane states with a known mathematical description. Research has already been conducted to verify the method for the extreme states and it has produced very good results. Invented new technique to 3D modeling of any shape of the flaccid membrane with well-known geometric dimensions allowed verifying the method for any shape of the membrane. The real membrane was replaced in sequence with four different rigid models with the known geometric dimensions. Results obtained in the study were presented.
The new innovative Depth from Defocus (DFD) method was used to visual measurement of the stroke volume of the extracorporeal pneumatic heart assist pump. The heart pump developed in the framework of the Polish Artificial Heart is the object of the study. However, the current studies are conducted on its adequate model. Using this model is justified because of the significant costs of the original prosthesis. The model was equipped with an adapter to mount the camera. This makes it possible to observe the surface of the membrane from the pneumatic chamber side without obstructing its normal operation, in particular without affecting the blood chamber. The model was designed in CAD software then it was 3D printed. The momentary surface shape of the flaccid membrane affects the volume of the blood chamber. The difficulty of the accuracy verification of the shape mapping is that heart assist pump fitted with a flaccid membrane has only two membrane states with a known mathematical description. Using reverse engineering, the authors have invented new technique to 3D modeling of any surface shape of the flaccid membrane with well-known geometric dimensions. The rigid models of different membrane states were designed in CAD software and printed on a 3D printer. The process of modeling and 3D printing and ready prototypes were presented.
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.
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.
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