An automatic biomedical acquisition system for hospital registration

Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This publication is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 954783. Background Stereotactic arrhythmia radio-ablation (STAR) is a promising strategy for the non-invasive treatment of ventricular arrhythmias (VA). The management of the cardio-respiratory motion of the target and the reduction of the uncertainties related to patients’ positioning are two of the main challenges that STAR has to overcome. A prototype of a system was developed that can automatically acquire and interpret echocardiographic images using an artificial intelligence (AI) algorithm to calculate cardiac displacement in real-time. Purpose To evaluate the feasibility of this automatic acquisition system in patients with a history of VA. Methods We conducted a single center, feasibility study enrolling consecutive patients with a history of VA. Echocardiographic images were automatically acquired from the parasternal and apical views with a dedicated probe. The system was designed to hold the probe fixed to the chest in the supine position during both free-breathing and short expiratory breath-hold sequences, to simulate STAR treatment. The primary endpoint was the percentage of patients reaching a score ≥2 in a multi-parametric assessment evaluating the quality of automatically acquired images in terms of: A - allowing a proper identification of the cardiac cycle phase using the AI algorithm, B - allowing a correct measurement of the heart displacement by the AI algorithm, C - ability to visually distinguish typical cardiac structures, and D - stability of the image throughout the respiration cycle. Moreover, we investigated the potential impact of clinical and demographic characteristics on achieving the primary outcome. Results From May to September 2021, we enrolled 24 patients (63±14 years, 21% females). All of them had a history of VA and 21 (88%) had an ICD. Eight patients (33%) had coronary artery disease, 12 (50%) had non-ischemic cardiomyopathy, and 3 had idiopathic VA. Parasternal as well as apical images were obtained from all patients except from one, in whom parasternal view could not be collected due to the patient’s inability to maintain the supine position. The primary outcome was achieved in 23 patients (96%) for the apical view, in 20 patients (87%) for the parasternal view, and in all patients in at least one of the two views. The images quality was maximal (i.e. score=4) in at least one of the two windows in 19 patients (79%). Atrial fibrillation arrhythmia was the only clinical characteristics associated with a poor score outcome in both imaging windows (apical p=0,022, parasternal p=0,014). Conclusion An automatic ultrasonographic image acquisition system associated with an AI algorithm is feasible for real-time monitoring of cardiac motion in patients with a history of VA. The possibility of real-time, non-invasive monitoring of cardiac position would lead to a significant improvement in the quality and safety of STAR treatment, particularly in case of treatment with heavy particles such as protons and carbon ions.

Automatic Multiple Sensor Data Acquisition System in a Real-time Production Environment

Real-time perception of rock–machine interaction information in TBM tunnelling using muck image analysis

An inexpensive data acquisition system for a multi-bed intensive care unit

In order to do the deformation characteristic tests on marble of which the geostress level is above 60MPa, a set of rigid pressure plates test equipment for center hole method and an automatic servo and acquisition system is developed. It consists of power transmission system, servo load system and measurement system. This paper mainly introduces the system structure, working principle and functions. It is shown by the application in a deep buried tunnel in a hydropower project that the equipment system has high loads, high precision, stable, reliable, and easy to operate. It can solve rock mass deformation test question under high stress and achieve good application effect.

Computerized automatic system to obtain inspiration/expiration chest roentgenograms without patient collaboration

An automatic microscope image acquisition, evaluation, and recognition system was developed for the analysis of Utermöhl plankton chambers in terms of taxonomic algae recognition. The system called PLASA (Plankton Structure Analysis) comprises (1) fully automatic archiving (optical fixation) of aqueous specimens as digital bright field and fluorescence images, (2) phytoplankton analysis and recognition, and (3) training facilities for new taxa. It enables characterization of aqueous specimens by their populations. The system is described in detail with emphasis on image analytical aspects. Plankton chambers are scanned by sizable grids, divers objective(s), and up to four fluorescence spectral bands. Acquisition positions are focused and digitized by a TV camera and archived on disk. The image data sets are evaluated by a large set of quantitative features. Automatic classifications for a number of organisms are developed and embedded in the program. Interactive programs for the design of training sets were additionally implemented. A long-term sampling period of 23 weeks from two ponds at two different locations each was performed to generate a reliable data set for training and testing purposes. These data were used to present this system's results for phytoplankton structure characterization. PLASA represents an automatic system, comprising all steps from specimen processing to algae identification up to species level and quantification.

This paper presents the design, sensor selection, circuitry, firmware development, and testing of an ultrasonicbased digital height meter. An Atmega328 microcontroller is used in the design to handle sensor measurements as it investigates the utilization of HC-SR04 ultrasonic sensor technology. Firmware was developed in the Arduino IDE environment, and the sketch was uploaded to the microcontroller. The designed circuit was constructed on a Veroboard, and the casing was designed for convenience of use. Ultrasonic digital height meters are more accurate, dependable, and quick when compared to hospital meter rules. The apparatus was mounted at a height of 2 meters to ease the measurement of humans. Results from the measurement of nine people were compared with those of the hospital scale, and a percentage error of 0.55% was obtained. A digital height meter can be a very useful instrument for many different applications, including medical, educational, engineering, and surveying, with careful planning and implementation.

Automatic eddy current signal acquisition system : 39496 Bailey, D.M. International Advances in Nondestructive Testing, Vol. 13, pp. 295–310 (1987). Edited by W.J. McGonnagle. Gordon and Breach Science Publishers.

Texas Instruments (TI) is developing the Aladdin computer under contract with the U. S. Army Communications and Electronics Command (CECOM). The program is sponsored by the Defense Advanced Research Projects Agency (DARPA) and the U. S. Army Night Vision and Electro-Optics Directorate (NVEOD). Processors currently available for today's advanced weapons systems are limited in their real-time processing capabilities and are generally specific to a selected mission. The lack of availability of a high performance, general purpose, programmable processor in a small volume applicable to a variety of weapons systems applications creates a high non-recurring development cost for each new program. Automatic target acquisition systems are specifically in need of processors that meet the required real- time processing throughput of a variety of algorithms within very restrictive volume constraints. The objective of the Aladdin program is to develop a very high performance miniature processor that fits within a 75 cubic inch cylindrical volume, and is easily programmable to provide the ability to detect, recognize, identify, and locate the optimal aimpoint of a target or targets.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper proposes an automatic knowledge acquisition system that includes mechanisms for generating fuzzy partitions, inducing fuzzy decision trees and inferring fuzzy classifications. Both discretizer and inducer designing need a dissimilarity measure to choose the appropriate partitions and the most significant predictors among the candi-date ones. Although current approa-ches use the entropy as a measure, our study focuses on adapting a c2 distance in order to accommodate a probabilistic test with a fuzzy data description. Summarizing such data within fuzzy contingency tables provides formal support to apply the c2-test for indepen-dence. The advantage of using a c2-based measure instead of an entropy-based one is to control probabilistically the partitioning as well as the splitting mechanisms. However, handling accu-rately the test procedure in fuzzy context needs restricting the practicable covering schemata for allowing the interpretation of membership degree vectors in terms of probability distribu-tions. Finally, the fuzzy inducer can be employed to build fuzzy classifiers, namely to apply a fuzzy inference mechanism in order to classify new (unseen) cases. Experimental eviden-ces derived from comparative tests confirm that a c2-based inducer produces more accurate and reliable results than an entropy-based one.

Recent work investigating excitation effects on an acoustically excited jet flow is reported. Emphasis is placed on integrated visualization and high-resolution and digital image processing, sequential planar gas concentrations and some characteristics of the large-scale vortical structures of acoustically excited jet flow, such as multiple-eddy merging, vortex-braids formation, eddy evolution and entrainment processes, jet-boundary expansion, etc. The digital image processing technique employed here extends our previous work (Chao et al. 1990) to optimal threshold filtering of the background noise and in situ calibration of camera and illumination distortions. A compact, low-cost, automatic frame acquisition and analysis system is developed for mean and r.m.s. planar gas concentrations and automatic jet-boundary identification. Also, stroboscopic images are created for detailed sequential study of a quick-changing process using a low framing-rate camera by suitably controlling the acoustic excitation frequency and the jet flow.

In the age of ever-increasing "-omics" studies, the accurate and statistically robust determination of microbial cell numbers within often-complex samples remains a key task in microbial ecology. Microscopic quantification is still the only method to enumerate specific subgroups of microbial clades within complex communities by, for example, fluorescence in situ hybridization (FISH). In this study, we improved an existing automatic image acquisition and cell enumeration system and adapted it for usage at high seas on board an oceanographic research ship. The system was evaluated by testing settings such as minimal pixel area and image exposure times ashore under stable laboratory conditions before being brought on board and tested under various wind and wave conditions. The system was robust enough to produce high-quality images even with ship heaves of up to 3 m and pitch and roll angles of up to 6.3°. On board the research ship, on average, 25% of the images acquired from plankton samples on filter membranes could be used for cell enumeration. Automated enumeration was highly correlated with manual counts (r(2) > 0.9). Even the smallest of microbial cells in the open ocean, members of the alphaproteobacterial SAR11 clade, could be confidently detected and enumerated. The automated image acquisition and cell enumeration system developed here enables an accurate and reproducible determination of microbial cell counts in planktonic samples and allows insight into the abundance and distribution of specific microorganisms already on board within a few hours.IMPORTANCE In this research article, we report on a new system and software pipeline, which allows for an easy and quick image acquisition and the subsequent enumeration of cells in the acquired images. We put this pipeline through vigorous testing and compared it to manual microscopy counts of microbial cells on membrane filters. Furthermore, we tested this system at sea on board a marine research vessel and counted bacteria on board within a few hours after the retrieval of water samples. The imaging and counting system described here has been successfully applied to a number of laboratory-based studies and allowed the quantification of thousands of samples and FISH preparations (see, e.g., H. Teeling, B. M. Fuchs, D. Becher, C. Klockow, A. Gardebrecht, C. M. Bennke, M. Kassabgy, S. Huang, A. J. Mann, J. Waldmann, M. Weber, A. Klindworth, A. Otto, J. Lange, J. Bernhardt, C. Reinsch, M. Hecker, J. Peplies, F. D. Bockelmann, U. Callies, G. Gerdts, A. Wichels, K. H. Wiltshire, F. O. Glöckner, T. Schweder, and R. Amann, Science 336:608-611, 2012, http://dx.doi.org/10.1126/science.1218344). We adjusted the standard image acquisition software to withstand ship movements. This system will allow for more targeted sampling of the microbial community, leading to a better understanding of the role of microorganisms in the global oceans.

In this paper, we focus on the student's “motivation level” in his learning situation, and we propose the ergonomic design of ITS framework as the motivation system. The aim of this system is motivating the student for his/her learning process to give the appropriate encouragement, praise or reproach messages. It is important to represent the student's internal psychological state. Therefore, we propose the human model which consists of several element for pshycological characteristics and prepares the fuzzy if-then rules to infer the message policy as the adequate strategy knowledge. In general, it is difficult to identify the fuzzy if-then rules and membership functions, so we introduce the automatic fuzzy rule acquisition system, called FREGA, which is our new knowledge acquisition system combining ID3 method and Genetic Algorithm. Finally, we give the estimation of this system.

Specific emitter identification is a technique that distinguishes different emitters using radio fingerprints. Feature extraction and classifier selection are critical factors affecting SEI performance. In this paper, we propose an SEI method using the Bispectrum-Radon transform (BRT) and a hybrid deep model. We propose BRT to characterize the unintentional modulation of pulses due to the superiority of bispectrum distributions in characterizing nonlinear features of signals. We then apply a hybrid deep model based on denoising autoencoders and a deep belief network to perform further deep feature extraction and discriminative identification. We design an automatic dependent surveillance-broadcast signal acquisition system to capture signals and to build dataset for validating our proposed SEI method. Theoretical analysis and experimental results show that the BRT feature outperformed traditional features in characterizing UMOP, and our proposed SEI method outperformed other feature and classifier combination methods.