Certain post-thoracic surgery complications are monitored in a standard manner using methods that employ ionising radiation. A need to automatise the diagnostic procedure has now arisen following the clinical trial of a novel lung ultrasound examination procedure that can replace X-rays. Deep learning was used as a powerful tool for lung ultrasound analysis. We present a novel deep-learning method, automated M-mode classification, to detect the absence of lung sliding motion in lung ultrasound. Automated M-mode classification leverages semantic segmentation to select 2D slices across the temporal dimension of the video recording. These 2D slices are the input for a convolutional neural network, and the output of the neural network indicates the presence or absence of lung sliding in the given time slot. We aggregate the partial predictions over the entire video recording to determine whether the subject has developed post-surgery complications. With a 64-frame version of this architecture, we detected lung sliding on average with a balanced accuracy of 89%, sensitivity of 82%, and specificity of 92%. Automated M-mode classification is suitable for lung sliding detection from clinical lung ultrasound videos. Furthermore, in lung ultrasound videos, we recommend using time windows between 0.53 and 2.13 s for the classification of lung sliding motion followed by aggregation.

This research investigates the suitability of printed polyamide 12 (PA12) and its dyed version to support cells in bioengineering applications. For this purpose, human gingival fibroblasts (hGF06) were cultured on PA-12 scaffolds that were 3D-printed by Multi Jet Fusion (MJF). The study examined the direct cultivation of cells on MJF-printed cell culture scaffolds and the effect of leachate of PA-12 printed by MJF on the cultured cells. The article presents research on the surface treatment of PA12 material used in 3D printing and the effect of automatic staining on cell vitality and proliferation in vitro. The study presents a unique device designed exclusively for staining prints made of the biocompatible material PA12 and demonstrates the compatibility of 3D-printed polyamide 12 parts stained in the novel device with a nutrient culture medium and cells. This novel PA12 surface treatment for biomedical purposes does not affect the compatibility with the culture medium, which is essential for cell viability and proliferation. Fluorescence microscopy revealed that mitochondrial fitness and cell survival were not affected by prolonged incubation with clear or dyed PA12 3D-printed parts.

We have developed a device, the Rehapiano, for the fast and quantitative assessment of action tremor. It uses strain gauges to measure force exerted by individual fingers. This article verifies the device’s capability to measure and monitor the development of upper limb tremor. The Rehapiano uses a precision, 24-bit, analog-to-digital converter and an Arduino microcomputer to transfer raw data via a USB interface to a computer for processing, database storage, and evaluation. First, our experiments validated the device by measuring simulated tremors with known frequencies. Second, we created a measurement protocol, which we used to measure and compare healthy patients and patients with Parkinson’s disease. Finally, we evaluated the repeatability of a quantitative assessment. We verified our hypothesis that the Rehapiano is able to detect force changes, and our experimental results confirmed that our system is capable of measuring action tremor. The Rehapiano is also sensitive enough to enable the quantification of Parkinsonian tremors.

The increasing demand for dental aesthetics, articulation corrections, and solutions for pain and frequent bruxism demands quick and effective restorative dental management. The biomedical research aimed to create a beneficial, ecological, and readily available anterior deprogrammer to determine the centric relation (CR) of cases. This medical device is additively manufactured from a biocompatible material. Size is customizable based on the width of the patient’s anterior central incisors. This is a pilot study with two subjects. The task was to develop a complete data protocol for the production process, computer-aided design (CAD), and three-dimensional (3D) printing of the anterior deprogrammers. The research focused on creating simple and practically applicable tools for the dentist’s prescription (anterior deprogrammer in three sizes), and secondly for the communication between the dentist and the patient (computer application). The tested hypothesis was whether, according to these novel tools, it is possible to produce functional occlusal splints, which could be manufactured using current technologies. This study compared a traditional splint with a digitally designed and 3D-printed one. The tested hypothesis was whether manufactured occlusal splints differ in patients’ subjective perception of comfort. Each conservative treatment was monitored for ten weeks. Initial results are promising; no statistically significant difference was found between the productive technologies.

In this review article, we would like to describe the development and production of equipment called MorPa, designed for pickling of components extruded from Polyamide 12 material using multi jet fusion technology. The goal of this project is to create an affordable and reliable device that will change color and physical properties of the components. In the following article, we describe the hardware part of the device, the software part and compare the printed parts before and after pickling. The article also includes a description of the control of the device based on the Arduino microcomputer with the used peripherals.

The purpose of this paper is to monitor the influence of the light spectrum on sleep quality. The theoretical part of the thesis is based on current research on sleep quality. The work is focused on the influence of the light spectrum on sleep. Sleep is monitored by a bracelet and the change of the light spectrum is ensured by an RGB light band. The secondary goal is to measure the influence of external factors on sleep. The investigated factors are CO2 level, TVOC, humidity and ambient temperature. External influences are measured by commonly available sensors. An Arduino microcomputer is used to collect data and control the RGB light.