This work analyzes the results of measurements on thermal energy harvesting through a wearable Thermo-electric Generator (TEG) placed on the arms and legs. Four large skin areas were chosen as locations for the placement of the TEGs. In order to place the generator on the body, a special manufactured band guaranteed the proper contact between the skin and TEG. Preliminary measurements were performed to find out the value of the resistor load which maximizes the power output. Then, an experimental investigation was conducted for the measurement of harvested energy while users were performing daily activities, such as sitting, walking, jogging, and riding a bike. The generated power values were in the range from 5 to 50 μW. Moreover, a preliminary hypothesis based on the obtained results indicates the possibility to use TEGs on leg for the recognition of locomotion activities. It is due to the rather high and different biomechanical work, produced by the gastrocnemius muscle, while the user is walking rather than jogging or riding a bike. This result reflects a difference between temperatures associated with the performance of different activities.

In the Czech Republic, the medical device industry is an important sector with a strong tradition and has high added value and perspectives in demand under changing demographic and social structures. The aim of this article is to describe and analyze the complex issues of the new European Commission Medical Device Regulation (MDR) 2017/745 from the perspective of the strategic decisions of companies that have to comply with the requirements imposed on them by the new legislation and at the same time fulfill their own business needs and goals. The legislative changes significantly affect the standards, processes, and certifications in the medical device sector. The classification system of medical devices has been revised to more appropriately reflect the possible health risks associated with use of modern high-end technology in healthcare. The requirement is to categorize each device under the highest possible risk class, which means for the medical device manufacturers to carefully review the new rules and regulations and classify their devices accordingly.

Background: Continuous non-invasive blood pressure (BP) measurement is a desired virtue in clinical practice. Unfortunately, current systems do not allow one for continuous, reliable BP measurement for more than a few hours per day, and they often require a complicated set of sensors to provide the necessary biosignals. Therefore we investigated the possibility of proposing a computational model that would predict the BP from pulse waves recorded in a single spot. Methods: Two experimental circuits were created. One containing a simple plastic tube for model development and a second with a silicone molded patient-specific arterial tree model. The first model served for the measuring of pulse waves under various BP (70–270 mmHg) and heart rate (60–190 beats per minute) values. Four different computational models were used to estimate the BP values from the diastolic time. The most accurate model was further validated using data from the latter experimental circuit containing a molded patient-specific silicone arterial tree. The measured data were averaged over a window of one, three, and five cycles. Two models based on pulse arrival time (PAT) were also analyzed for comparison. Results: The most accurate model exhibits a correlation coefficient of r = 0.967. The Bland–Altman plot revealed standard deviations (SD) between the model predictions and measurement of 10, 8.3, and 7.5 mmHg for the systolic BP and 8.7, 7 and 6.3 mmHg for the diastolic BP (both pressures calculated for the averaging windows of one, three, and five cycles, respectively). The best of the used PAT based model exhibited a SD of 17, 16, and 15 mmHg for the systolic BP and 14, 13, and 12 mmHg for the diastolic BP for the same averaging windows. Discussion: The proposed model showed its capability to predict BP accurately from the shape of the pulse wave measured at a single spot. Its SD was about 50% lower compared to the PAT based models which met the requirements of the Association for the Advancement of Medical Instrumentation.

The development of a new product is essential for the progress and success of any company. The medical device market is very specific, which is challenging. Therefore, this paper assesses an economic model for medical device evaluation using the economic, health, technology regulatory, and present market knowledge to enable the cost–time conception for any applicant. The purpose of this study is to propose a comprehensive stage model of the medical device development to subsequently describe the financial expenditure of the entire development process. The identification of critical steps was based on the literature review, and analysis, and a comparison of the available medical device development stages and directives. Furthermore, a preliminary assessment of the medical device development steps and procedures on the basis of the interviews was performed. Six interviews were conducted with an average duration of one hour, focusing on areas: relevance and level of detail of the medical device development stages, involvement of economic methods, and applicability of the proposed model. Subsequently, the improvement and modification of the medical device investment process, based on respondents’ responses, were conducted. The authors have proposed the complexity model MedDee—Medical Devices Development by Economic Evaluation. This model is comprised of six phases: initiation, concept, design, production, final verification, and market disposition in which the economic methods are incorporated.

Plant growth-promoting rhizobacteria (PGPR) are eco-friendly and sustainable options for agrochemicals, particularly for enhancing crop productivity under stress conditions. The present research aims to isolate and characterize native PGPR from tomato rhizospheric soil and to evaluate their effectiveness as a dose-dependent response to enhance the growth of tomato seedlings. Out of 112 isolates, 10 bacterial strains were selected based on key PGPR traits, including indole-3-acetic acid (IAA), ammonia production, hydrogen cyanide (HCN), exopolysaccharide (EPS) synthesis, hydrolytic enzyme activity, potassium solubilization, antifungal activity against Fusarium oxysporum, and tolerance to pH and heat stress. Molecular identification via 16S rRNA gene sequencing confirmed that these isolates belong to the genera Serratia and Enterobacter. S. marcescens So-1 and Enterobacter sp. So-12 produced the highest levels of IAA (2.6–24.1 µg/mL). In vitro tomato seed germination tests using bacterial suspensions at three concentrations (10⁶, 10⁷, and 10⁸ CFU/mL) showed dose-dependent improvements, with T1 increasing germination up to 108.3% compared to the control. In polyhouse trials using cocopeat formulations, seedling growth improved noticeably. T2 increased the root length (28.3 ± 2.98 cm) by over 1560%, and the shoot length (35.7 ± 0.57 cm) increased by 55% against the control, whose root length is 1.7 ± 0.47. The chlorophyll amount of the treated leaves further showed significant results over the control. Collectively, these findings suggest that using native PGPR in a dose-dependent way can help tomato seedlings grow better and promote more sustainable crop production.