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Within the literature concerning modern machine learning techniques applied to the medical field, there is a growing interest in the application of these technologies to the nephrological area, especially regarding the study of renal pathologies, because they are very common and widespread in our society, afflicting a high percentage of the population and leading to various complications, up to death in some cases. For these reasons, the authors have considered it appropriate to collect, using one of the major bibliographic databases available, and analyze the studies carried out until February 2022 on the use of machine learning techniques in the nephrological field, grouping them according to the addressed pathologies: renal masses, acute kidney injury, chronic kidney disease, kidney stone, glomerular disease, kidney transplant, and others less widespread. Of a total of 224 studies, 59 were analyzed according to inclusion and exclusion criteria in this review, considering the method used and the type of data available. Based on the study conducted, it is possible to see a growing trend and interest in the use of machine learning applications in nephrology, becoming an additional tool for physicians, which can enable them to make more accurate and faster diagnoses, although there remains a major limitation given the difficulty in creating public databases that can be used by the scientific community to corroborate and eventually make a positive contribution in this area. [ABSTRACT FROM AUTHOR]

One of the most important parameters to be controlled during the production of textile yarns obtained by mixing pre-colored fibers, is the color correspondence between the manufactured yarn and a given reference, usually provided by a designer or a customer. Obtaining yarns from raw pre-colored fibers is a complex manufacturing process entailing a number of steps such as laboratory sampling, color recipe corrections, blowing, carding and spinning. Carding process is the one devoted to transform a “fuzzy mass” of tufted fibers into a regular mass of untwisted fibers, named “tow”. During this process, unfortunately, the correspondence between the color of the tow and the target one cannot be assured, thus leading to yarns whose color differs from the one used for reference. To solve this issue, the main aim of this work is to provide a system able to perform a spectral camera-based real-time measurement of a carded tow, to assess its color correspondence with a reference carded fabric and, at the same time, to monitor the overall quality of the tow during the carding process. Tested against a number of differently colored carded fabrics, the proposed system proved its effectiveness in reliably assessing color correspondence in real-time. [ABSTRACT FROM AUTHOR]

Nowadays, the creation of methodologies and tools for facilitating the 3D reproduction of artworks and, contextually, to make their exploration possible and more meaningful for blind users is becoming increasingly relevant in society. Accordingly, the creation of integrated systems including both tactile media (e.g., bas-reliefs) and interfaces capable of providing the users with an experience cognitively comparable to the one originally envisioned by the artist, may be considered the next step for enhancing artworks exploration. In light of this, the present work provides a description of a first-attempt system designed to aid blind people (BP) in the tactile exploration of bas-reliefs. In detail, consistent hardware layout, comprising a hand-tracking system based on Kinect® sensor and an audio device, together with a number of methodologies, algorithms and information related to physical design are proposed. Moreover, according to experimental test on the developed system related to the device position, some design alternatives are suggested so as to discuss pros and cons. [ABSTRACT FROM AUTHOR]

Home-based rehabilitation is becoming a gold standard for patient who have undergone knee arthroplasty or full knee replacement, as it helps healthcare costs to be minimized. Nevertheless, there is a chance of increasing adverse health effects in case of home care, primarily due to the patients' lack of motivation and the doctors' difficulty in carrying out rigorous supervision. The development of devices to assess the efficient recovery of the operated joint is highly valued both for the patient, who feels encouraged to perform the proper number of activities, and for the doctor, who can track him/her remotely. Accordingly, this paper introduces an interactive approach to angular range calculation of hip and knee joints based on the use of low-cost devices which can be operated at home. First, the patient's body posture is estimated using a 2D acquisition method. Subsequently, the 3D posture is evaluated by using the depth information coming from an RGB-D sensor. Preliminary results show that the proposed method effectively overcomes many limitations by fusing the results obtained by the state-of-the-art robust 2D pose estimation algorithms with the 3D data of depth cameras by allowing the patient to be correctly tracked during rehabilitation exercises. [ABSTRACT FROM AUTHOR]

RGB-D cameras are employed in several research fields and application scenarios. Choosing the most appropriate sensor has been made more difficult by the increasing offer of available products. Due to the novelty of RGB-D technologies, there was a lack of tools to measure and compare performances of this type of sensor from a metrological perspective. The recent ISO 10360-13:2021 represents the most advanced international standard regulating metrological characterization of coordinate measuring systems. Part 13, specifically, considers 3D optical sensors. This paper applies the methodology of ISO 10360-13 for the characterization and comparison of three RGB-D cameras produced by Intel® RealSense™ (D415, D455, L515) in the close range (100–1500 mm). ISO 10360-13 procedures, which focus on metrological performances, are integrated with additional tests to evaluate systematic errors (acquisition of flat objects, 3D reconstruction of objects). The present paper proposes an off-the-shelf comparison which considers the performance of the sensors throughout their acquisition volume. Results have exposed the strengths and weaknesses of each device. The D415 device showed better reconstruction quality on tests strictly related to the short range. The L515 device performed better on systematic depth errors; finally, the D455 device achieved better results on tests related to the standard. [ABSTRACT FROM AUTHOR]

Designing an acquisition system for 2D or 3D information, based on the integration of data provided by different sensors is a task that requires a labor-intensive initial design phase. Indeed, the definition of the architecture of such acquisition systems needs to start from the identification of the position and orientation of the sensors observing the scene. Their placement is carefully studied to enhance the efficacy of the system. This often coincides with the need to maximize the surfaces observed by the sensors or some other metric. An automatic optimization procedure based on the Particle Swarm Optimization (PSO) algorithm, to seek the most convenient setting of multiple optical sensors observing a 3D scene, is proposed. The procedure has been developed to provide a fast and efficient tool for 2D and 3D data acquisition. Three different objective functions of general validity, to be used in future applications, are proposed and described in the text. Various filters are introduced to reduce computational times of the whole procedure. The method is capable of handling occlusions from undesired obstacle in the scene. Finally, the entire method is discussed with reference to 1) the development of a body scanner for the arm-wrist-hand district and 2) the acquisition of an internal environment as case studies. [ABSTRACT FROM AUTHOR]

Low-cost RGB-D cameras are increasingly being used in several research fields, including human–machine interaction, safety, robotics, biomedical engineering and even reverse engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras have proven to be among the most suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e., ~160–10,000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations for the RealSense D415. In particular, tests are carried out to assess the device performance in the near range (i.e., 100–1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e., the German VDI/VDE 2634 Part 2) with a number of literature-based strategies. Performance analysis is finally compared against the latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in reverse engineering applications. [ABSTRACT FROM AUTHOR]