Search Results (8)

Cardiometabolic diseases (CMDs) are interrelated and multifactorial conditions, including arterial hypertension, type 2 diabetes, heart failure, coronary artery disease, and stroke. Due to the burden of cardiovascular morbidity and mortality associated with CMDs’ increasing prevalence, there is a critical need for novel diagnostic and therapeutic strategies in their management. In clinical practice, innovative methods such as epicardial adipose tissue evaluation, ventricular–arterial coupling, and exercise tolerance studies could help to elucidate the multifaceted mechanisms associated with CMDs. Similarly, epigenetic changes involving noncoding RNAs, chromatin modulation, and cellular senescence could represent both novel biomarkers and targets for CMDs. Despite the promising data available, significant challenges remain in translating basic research findings into clinical practice, highlighting the need for further investigation into the complex pathophysiology underlying CMDs. Full article

Across different fields within robotics, there is a great need for lightweight, efficient actuators with human-like performance. Linkage-based passive variable transmissions and torque-sensitive transmissions have emerged as promising solutions to meet this need by significantly increasing actuator efficiency and power density, but their modeling and analysis remain an open research topic. In this paper, we introduce the sensitivity between input displacement and output torque as a key metric to analyze the performance of these complex mechanisms in dynamic tasks. We present the analytical model of sensitivity in the context of two different torque-sensitive transmission designs, and used this sensitivity metric to analyze the differences in their performance. Experiments with these designs implemented within a powered knee prosthesis were conducted, and results validated the sensitivity model as well as its role in predicting actuators’ dynamic performance. Together with other design methods, sensitivity analysis is a valuable tool for designers to systematically analyze and create transmission systems capable of human-like physical behavior. Full article

Human effects on the water economy of the river systems are currently well documented at the worldwide scale, impacting a range of ecosystem services. In this perspective article, we discuss the findings of recent papers that under different intensities of human disturbance have coupled the analyses of riverine geomorphological and plant community patterns. The discussion is carried out within the historical framework of past and current methods of sampling and analysing the river geomorphology and the plant communities along cross-sectional profiles. The research has been conducted along three major gravel-bed rivers of the south-eastern Italian Alps: Brenta, Piave, and Tagliamento. The collated and summarised results here demonstrate the existence of a strong relationship between the woody species variance that can be explained by geomorphologic patterns and human disturbance intensity. The less disturbed river has an intermediate value of species variance that can be explained by geomorphology, the intermediate-disturbed river has the highest value, and the highly disturbed river has the lowest value. Then, we proposed an interpretation key and an adaptation of the intermediate disturbance hypothesis, which reads as: “in rivers, the greatest influence of geomorphic properties on vegetation occurs in the moderate or middle ranges of a human disturbance gradient”. We argue that the “influence of the geomorphic properties on vegetation” is assessed through the species constrained variance through an ordination analysis, such as that which is explained here. The most recent collection techniques based on field survey and remote sensing are making it increasingly easy and accurate to study of the trends of geomorphic and plant community variables throughout time and space. Thus, we encourage that researchers should check whether and how our observation is conserved through different groups of taxa and intensities of natural and human disturbance. Full article

Many people struggle with mobility impairments due to lower limb amputations. To participate in society, they need to be able to walk on a wide variety of terrains, such as stairs, ramps, and level ground. Current lower limb powered prostheses require different control strategies for varying ambulation modes, and use data from mechanical sensors within the prosthesis to determine which ambulation mode the user is in. However, it can be challenging to distinguish between ambulation modes. Efforts have been made to improve classification accuracy by adding electromyography information, but this requires a large number of sensors, has a low signal-to-noise ratio, and cannot distinguish between superficial and deep muscle activations. An alternative sensing modality, A-mode ultrasound, can detect and distinguish between changes in superficial and deep muscles. It has also shown promising results in upper limb gesture classification. Despite these advantages, A-mode ultrasound has yet to be employed for lower limb activity classification. Here we show that A- mode ultrasound can classify ambulation mode with comparable, and in some cases, superior accuracy to mechanical sensing. In this study, seven transfemoral amputee subjects walked on an ambulation circuit while wearing A-mode ultrasound transducers, IMU sensors, and their passive prosthesis. The circuit consisted of sitting, standing, level-ground walking, ramp ascent, ramp descent, stair ascent, and stair descent, and a spatial–temporal convolutional network was trained to continuously classify these seven activities. Offline continuous classification with A-mode ultrasound alone was able to achieve an accuracy of $91.8\pm 3.4\%$, compared with $93.8\pm 3.0\%$, when using kinematic data alone. Combined kinematic and ultrasound produced $95.8\pm 2.3\%$ accuracy. This suggests that A-mode ultrasound provides additional useful information about the user’s gait beyond what is provided by mechanical sensors, and that it may be able to improve ambulation mode classification. By incorporating these sensors into powered prostheses, users may enjoy higher reliability for their prostheses, and more seamless transitions between ambulation modes. Full article

Sepsis is defined as a systemic inflammatory dysfunction strictly associated with infectious diseases, which represents an important health issue whose incidence is continuously increasing worldwide. Nowadays, sepsis is considered as one of the main causes of death that mainly affects critically ill patients in clinical settings, with a higher prevalence in low-income countries. Currently, sepsis management still represents an important challenge, since the use of traditional techniques for the diagnosis does not provide a rapid response, which is crucial for an effective infection management. Biosensing systems represent a valid alternative due to their characteristics such as low cost, portability, low response time, ease of use and suitability for point of care/need applications. This review provides an overview of the infectious agents associated with the development of sepsis and the host biomarkers suitable for diagnosis and prognosis. Special focus is given to the new emerging biosensing technologies using electrochemical and optical transduction techniques for sepsis diagnosis and management. Full article

The presence of injectors with strongly swirled flows, used to promote flame stability in the combustion chambers of gas turbines, influences the behaviour of the effusion cooling jets and consequently of the liner’s cooling capabilities. For this reason, unsteady behaviour of the jets in the presence of swirling flow requires a characterization by means of experimental flow field analyses. The experimental setup of this work consists of a non-reactive single-sector linear combustor test rig, scaled up with respect to the real engine geometry to increase spatial resolution and to reduce the frequencies of the unsteadiness. It is equipped with a radial swirler and multi-perforated effusion plates to simulate the liner cooling system. Two effusion plates were tested and compared: with cylindrical and with laid-back fan-shaped 7-7-7 holes in staggered arrangement. Time resolved Particle Image Velocimetry has been carried out: the unsteady characteristics of the jets, promoted by the intermittent interactions with the turbulent mainstream, have been investigated as their vortex structures and turbulent decay. The results demonstrate how an unsteady analysis is necessary to provide a complete characterization of the coolant behaviour and of its turbulent mixing with mainflow, which affect, in turn, the film cooling capability and liner’s lifetime. Full article

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant’Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant’Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted. Full article

A sensory apparatus to monitor pressure distribution on the physical human-robot interface of lower-limb exoskeletons is presented. We propose a distributed measure of the interaction pressure over the whole contact area between the user and the machine as an alternative measurement method of human-robot interaction. To obtain this measure, an array of newly-developed soft silicone pressure sensors is inserted between the limb and the mechanical interface that connects the robot to the user, in direct contact with the wearer’s skin. Compared to state-of-the-art measures, the advantage of this approach is that it allows for a distributed measure of the interaction pressure, which could be useful for the assessment of safety and comfort of human-robot interaction. This paper presents the new sensor and its characterization, and the development of an interaction measurement apparatus, which is applied to a lower-limb rehabilitation robot. The system is calibrated, and an example its use during a prototypical gait training task is presented. Full article