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Objectives Workers in the construction industry have been exposed to asbestos in various occupations. In Italy, a National Mesothelioma Registry has been implemented more than 20 years ago. Using cases selected from this registry and exploiting existing control data sets, we estimated relative risks for pleural mesothelioma (PM) among construction workers.Design Case–control study.Setting Cases from the National Mesothelioma Registry (2000–2018), controls from three previous case–control studies.Methods We selected male PM incident cases diagnosed in 2000–2018. Population controls were taken from three studies performed in six Italian regions within two periods (2002–2004 and 2012–2016). Age-adjusted and period-adjusted unconditional logistic regression models were fitted to estimate odds ratios (OR) for occupations in the construction industry. We followed two approaches, one (primary) excluding and the other (secondary) including subjects employed in other non-construction blue collar occupations for >5 years. For both approaches, we performed an overall analysis including all cases and, given the incomplete temporal and geographic overlap of cases and controls, three time or/and space restricted sensitivity analyses.Results The whole data set included 15 592 cases and 2210 controls. With the primary approach (4797 cases and 1085 controls), OR was 3.64 (2181 cases) for subjects ever employed in construction. We found elevated risks for blue-collar occupations (1993 cases, OR 4.52), including bricklayers (988 cases, OR 7.05), general construction workers (320 cases, OR 4.66), plumbers and pipe fitters (305 cases, OR 9.13), painters (104 cases, OR 2.17) and several others. Sensitivity analyses yielded very similar findings. Using the secondary approach, we observed similar patterns, but ORs were remarkably lower.Conclusions We found markedly increased PM risks for most occupations in the construction industry. These findings are relevant for compensation of subjects affected with mesothelioma in the construction industry.

Abstract Background Closing the control loop between users and their prostheses by providing artificial sensory feedback is a fundamental step toward the full restoration of lost sensory-motor functions. Methods We propose a novel approach to provide artificial proprioceptive feedback about two degrees of freedom using a single array of 8 vibration motors (compact solution). The performance afforded by the novel method during an online closed-loop control task was compared to that achieved using the conventional approach, in which the same information was conveyed using two arrays of 8 and 4 vibromotors (one array per degree of freedom), respectively. The new method employed Gaussian interpolation to modulate the intensity profile across a single array of vibration motors (compact feedback) to convey wrist rotation and hand aperture by adjusting the mean and standard deviation of the Gaussian, respectively. Ten able-bodied participants and four transradial amputees performed a target achievement control test by utilizing pattern recognition with compact and conventional vibrotactile feedback to control the Hannes prosthetic hand (test conditions). A second group of ten able-bodied participants performed the same experiment in control conditions with visual and auditory feedback as well as no-feedback. Results Conventional and compact approaches resulted in similar positioning accuracy, time and path efficiency, and total trial time. The comparison with control condition revealed that vibrational feedback was intuitive and useful, but also underlined the power of incidental feedback sources. Notably, amputee participants achieved similar performance to that of able-bodied participants. Conclusions The study therefore shows that the novel feedback strategy conveys useful information about prosthesis movements while reducing the number of motors without compromising performance. This is an important step toward the full integration of such an interface into a prosthesis socket for clinical use.

Lahars represent some of the most dangerous phenomena in volcanic areas for their destructive power, causing dramatic changes in the landscape with no premonitory signs and impacting the population and infrastructure. In this regard, the Campanian Plain turns out to be very prone to the development of these phenomena, since the slopes of the Somma–Vesuvius and Campi Flegrei volcanoes, along with the Apennine reliefs, are mantled by pyroclastic deposits that can be easily remobilized, especially after intense and/or prolonged rainfall. This study focuses on the analysis of pyroclastic fall and flow deposits and of the syn- and post-eruptive lahar deposits related to two sub-Plinian eruptions of Vesuvius in 472 CE (Pollena) and 1631. To begin with, historical and field data from the existing literature and from hundreds of outcrops were collected and organized into a database, which was integrated with several new pieces of data. In particular, stratigraphic, sedimentological (facies analysis and laboratory), and archeological analyses were carried out, in addition to rock magnetic investigations and impact parameter calculations. The new data are also referenced to the finding of ash beds in more distal areas, which were included in new isopach maps for the two sub-Plinian eruptions. The results show that for both eruptions the distribution of the primary deposits is wider than previously known. A consequence of these results is that a wider areal impact should be expected in terms of civil protection, as the sub-Plinian scenario is the reference one for a future large eruption of Vesuvius. Such a distribution of the pyroclastic deposits directly affects the one of the lahar deposits, also because a significant remobilization took place during and after the studied eruptions, which involved distal phreatomagmatic ash. From these integrated analyses, it was possible to constrain the timing of the deposition and the kind of deposits remobilized (pyroclastic fall vs. flow), and it was possible to calculate the velocities and dynamic pressures of the lahars and ultimately infer the lahar transport and emplacement mechanisms. The multidisciplinary approach adopted in this work shows how it is crucial to assess the impact of lahars in densely populated areas even at distances of several to tens of kilometers from active volcanoes. This especially applies to large parts of the densely populated areas around Somma–Vesuvius up to the nearby Apennine valleys.

In this paper we present a new model for the simulation of lahars based on the depth-averaged code IMEX-SfloW2D with new governing and constitutive equations introduced to better describe the dynamics of lahars. A thorough sensitivity analysis is carried out to identify the critical processes (such as erosion and deposition) and parameters (both numerical and physical) controlling lahar runout using both synthetic and real case topographies. In particular, an application of the model to a syn-eruptive lahar from a reference size eruption from Somma–Vesuvius, affecting the Campanian Plain (southern Italy), described in Di Vito et al. (2024), is used in this work for the sensitivity analysis. Effects of erosion and deposition are investigated by comparing simulations with and without these processes. By comparing flow thickness and area covered by the flow and their evolution with time, we show that the modelling of both the processes is important to properly simulate the effects of the bulking and debulking as well as the associated changes in rheology. From a computational point of view, the comparisons of simulations obtained for different numerical grids (from 25 to 100 m), scheme order, and grain size discretization were useful to find a good compromise between resolution and computational speed. The companion paper by Sandri et al. (2024) shows an application of the presented model for probabilistic volcanic hazard assessment for lahars from Vesuvius deposits in the Neapolitan area.

In this study we present a novel general methodology for probabilistic volcanic hazard assessment (PVHA) for lahars. We apply the methodology to perform a probabilistic assessment in the Campanian Plain (southern Italy), focusing on syn-eruptive lahars from a reference size eruption from Somma–Vesuvius. We take advantage of new field data relative to volcaniclastic flow deposits in the target region (Di Vito et al., 2024b) and recent improvements in modelling lahars (de' Michieli Vitturi et al., 2024). The former allowed defining proper probability density functions for the parameters related to the flow initial conditions, and the latter allowed computationally faster model runs. In this way, we are able to explore the effects of uncertainty in the initial flow conditions on the invasion of lahars in the target area by sampling coherent sets of values for the input model parameters and performing a large number of simulations. We also account for the uncertainty in the position of lahar generation by running the analysis on 11 different catchments threatening the Campanian Plain. The post-processing of the simulation outputs led to the production of hazard curves for the maximum flow thickness reached on a grid of points covering the Campanian Plain. By cutting the hazard curves at selected threshold values, we produce a portfolio of hazard maps and probability maps for the maximum flow thickness. We also produce hazard surface and probability maps for the simultaneous exceeding of pairs of thresholds in flow thickness and dynamic pressure. The latter hazard products represent, on one hand, a novel product in PVHA for lahars and, on the other hand, a useful means of impact assessment by assigning a probability to the occurrence of lahars that simultaneously have a relevant flow thickness and large dynamic pressure.

Abstract Explosivity of basaltic eruptions is related to the efficiency in which exsolved gas can separate from the melt during ascent, which is controlled by magma permeability. However, basaltic pyroclasts from eruptions of varying explosivity can show similar permeability, indicating a possible complex relationship between permeability, outgassing and eruptive style. Here, we provide 3D measurements of basaltic pyroclasts using X-ray microtomography. We investigate the role of permeability and outgassing on magma ascent dynamics by using a numerical conduit model. Among the permeable parameters, bubble number density and friction coefficient largely affect explosivity. However, for fast ascending basaltic magmas, gas-melt coupling is maintained independent of magma permeability. In this case, magma storage conditions may determine eruptive style, driving rapid magma ascent, crystallisation and bubble nucleation, producing a highly explosive eruption. Monitoring parameters which reveal pre-eruptive conditions may assist hazard mitigation, particularly for basaltic systems which exhibit a wide range in eruptive style.

Structured expert judgment is crucial when dealing with significant epistemic and aleatoric uncertainties, particularly in probabilistic hazard assessments, where decisions based on uncertain information are often critical. In structured expert elicitations, participants are asked to quantify their uncertainty judgments by providing their percentile estimates of numerical values for a set of questions. More specifically, performance-based elicitations start with “seed” questions for determining experts’ uncertainty quantification skill. The performance scores are thus used to define each expert’s weight to be applied when considering their judgments on “target” questions, i.e., the actual variables of interest for the case study. In this paper we describe ELICIPY, a new Python tool which allows to perform expert elicitation sessions in a framework that covers both the questionnaire collection and the analysis parts, an approach that simplifies the work normally done by the analyst(s). This is achieved through the automatic generation of online webforms to collect the experts’ answers, their check for consistency and, finally, their analysis using different weighting schemes. The tool automatically produces outputs in different formats and creates a pptx presentation file available just after the collection of the answers.

The robotics discipline is exploring precise and versatile solutions for upper-limb rehabilitation in Multiple Sclerosis (MS). People with MS can greatly benefit from robotic systems to help combat the complexities of this disease, which can impair the ability to perform activities of daily living (ADLs). In order to present the potential and the limitations of smart mechatronic devices in the mentioned clinical domain, this review is structured to propose a concise SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of robotic rehabilitation in MS. Through the SWOT Analysis, a method mostly adopted in business management, this paper addresses both internal and external factors that can promote or hinder the adoption of upper-limb rehabilitation robots in MS. Subsequently, it discusses how the synergy with another category of interaction technologies - the systems underlying virtual and augmented environments - may empower Strengths, overcome Weaknesses, expand Opportunities, and handle Threats in rehabilitation robotics for MS. The impactful adaptability of these digital settings (extensively used in rehabilitation for MS, even to approach ADL-like tasks in safe simulated contexts) is the main reason for presenting this approach to face the critical issues of the aforementioned SWOT Analysis. This methodological proposal aims at paving the way for devising further synergistic strategies based on the integration of medical robotic devices with other promising technologies to help upper-limb functional recovery in MS.

Prediction of major arrhythmic events (MAEs) in dilated cardiomyopathy represents an unmet clinical goal. Computational models and artificial intelligence (AI) are new technological tools that could offer a significant improvement in our ability to predict MAEs. In this proof-of-concept study, we propose a deep learning (DL)-based model, which we termed Deep ARrhythmic Prevention in dilated cardiomyopathy (DARP-D), built using multidimensional cardiac magnetic resonance data (cine videos and hypervideos and LGE images and hyperimages) and clinical covariates, aimed at predicting and tracking an individual patient's risk curve of MAEs (including sudden cardiac death, cardiac arrest due to ventricular fibrillation, sustained ventricular tachycardia lasting ≥30 s or causing haemodynamic collapse in

Large explosive eruptions of basaltic magma are promoted by low pre-eruptive temperatures in crystallising shallow magma reservoirs, according to an integrated petrological, geochemical and numerical modelling study.

Abstract Background Cybathlon championship aims at promoting the development of prosthetic and assistive devices capable to meet users’ needs. This paper describes and analyses possible exploitation outcomes of our team’s (REHAB TECH) experience into the Powered Arm Prosthesis Race of the Cybathlon 2020 Global Edition, with the novel prosthetic system Hannes. In detail, we present our analysis on a concurrent evaluation conducted to verify if the Cybathlon training and competition positively influenced pilot’s performance and human-technology integration with Hannes, with respect to a non-runner Hannes user. Methods Two transradial amputees were recruited as pilots (Pilot 1 and Pilot 2) for the Cybathlon competition and were given the polyarticulated myoelectric prosthetic hand Hannes. Due to COVID-19 emergency, only Pilot 1 was trained for the race. However, both pilots kept Hannes for Home Use for seven weeks. Before this period, they both participated to the evaluation of functionality, embodiment, and user experience (UX) related to Hannes, which they repeated at the end of the Home Use and right after the competition. We analysed Pilot 1’s training and race outcomes, as well as changes in the concurrent evaluation, and compared these results with Pilot 2’s ones. Results The Cybathlon training gradually improved Pilot 1’s performances, leading to the sixth place with a single error in task 5. In the parallel evaluation, both pilots had an overall improvement over time, whereas Pilot 2 experienced a deterioration of embodiment. In detail, Pilot 1, who followed the training and raced the Cybathlon, improved in greater way. Conclusion Hannes demonstrated to be a valuable competitor and to perform grasps with human-like behaviors. The higher improvements of Pilot 1, who actively participated in the Cybathlon, in terms of functionality, embodiment and UX, may depend on his training and engagement in the effort of achieving a successful user-prosthesis interaction during the competition. Tasks based on Cybathlon’s ones could improve the training phase of a prosthetic user, stimulating dexterity, prosthetic integration, and user perception towards the prosthesis. Likewise, timed races or competitions could facilitate and accelerate the learning phase, improving the efficiency and efficacy of the process.

Abstract Background The inability of users to directly and intuitively control their state-of-the-art commercial prosthesis contributes to a low device acceptance rate. Since Electromyography (EMG)-based control has the potential to address those inabilities, research has flourished on investigating its incorporation in microprocessor-controlled lower limb prostheses (MLLPs). However, despite the proposed benefits of doing so, there is no clear explanation regarding the absence of a commercial product, in contrast to their upper limb counterparts. Objective and methodologies This manuscript aims to provide a comparative overview of EMG-driven control methods for MLLPs, to identify their prospects and limitations, and to formulate suggestions on future research and development. This is done by systematically reviewing academical studies on EMG MLLPs. In particular, this review is structured by considering four major topics: (1) type of neuro-control, which discusses methods that allow the nervous system to control prosthetic devices through the muscles; (2) type of EMG-driven controllers, which defines the different classes of EMG controllers proposed in the literature; (3) type of neural input and processing, which describes how EMG-driven controllers are implemented; (4) type of performance assessment, which reports the performance of the current state of the art controllers. Results and conclusions The obtained results show that the lack of quantitative and standardized measures hinders the possibility to analytically compare the performances of different EMG-driven controllers. In relation to this issue, the real efficacy of EMG-driven controllers for MLLPs have yet to be validated. Nevertheless, in anticipation of the development of a standardized approach for validating EMG MLLPs, the literature suggests that combining multiple neuro-controller types has the potential to develop a more seamless and reliable EMG-driven control. This solution has the promise to retain the high performance of the currently employed non-EMG-driven controllers for rhythmic activities such as walking, whilst improving the performance of volitional activities such as task switching or non-repetitive movements. Although EMG-driven controllers suffer from many drawbacks, such as high sensitivity to noise, recent progress in invasive neural interfaces for prosthetic control (bionics) will allow to build a more reliable connection between the user and the MLLPs. Therefore, advancements in powered MLLPs with integrated EMG-driven control have the potential to strongly reduce the effects of psychosomatic conditions and musculoskeletal degenerative pathologies that are currently affecting lower limb amputees.

Numerical simulations of volcanic processes play a fundamental role in understanding the dynamics of magma storage, ascent, and eruption. The recent extraordinary progress in computer performance and improvements in numerical modeling techniques allow simulating multiphase systems in mechanical and thermodynamical disequilibrium. Nonetheless, the growing complexity of these simulations requires the development of flexible computational tools that can easily switch between sub-models and solution techniques. In this work we present MagmaFOAM, a library based on the open-source computational fluid dynamics software OpenFOAM that incorporates models for solving the dynamics of multiphase, multicomponent magmatic systems. Retaining the modular structure of OpenFOAM, MagmaFOAM allows runtime selection of the solution technique depending on the physics of the specific process and sets a solid framework for in-house and community model development, testing, and comparison. MagmaFOAM models thermomechanical nonequilibrium phase coupling and phase change, and it implements state-of-the-art multiple volatile saturation models and constitutive equations with composition-dependent and space–time local computation of thermodynamic and transport properties. Code testing is performed using different multiphase modeling approaches for processes relevant to magmatic systems: Rayleigh–Taylor instability for buoyancy-driven magmatic processes, multiphase shock tube simulations propaedeutical to conduit dynamics studies, and bubble growth and breakage in basaltic melts. Benchmark simulations illustrate the capabilities and potential of MagmaFOAM to account for the variety of nonlinear physical and thermodynamical processes characterizing the dynamics of volcanic systems.

Abstract To evaluate the incidence of COVID-19 infection in health care workers from the start of the COVID-19 pandemic in NE Italy, vaccination with BNT162b2. This was a retrospective cohort study. Healthcare workers were routinely tested for SARS-CoV-2 infection using real-time polymerase chain reaction tests in nasopharyngeal swabs. Logistic regression was used to calculate the incidence rate ratios (IRRs) of the factors associated with COVID-19. A total of 4251 workers were followed up, and the prevalence of COVID-19 was 13.6%. In March 2021 the incidence of infection was 4.88 and 103.55 cases for 100,000 person-days in vaccinated and non-vaccinated workers, respectively, with an adjusted IRRs of 0.05 (95% CI 0.02–0.08). Our study evaluated the monthly incidence in health care workers in Trieste hospitals before and after vaccination, finding an estimated vaccine effectiveness of 95% in health care workers routinely tested.

Abstract Background Acquired brain injuries, such as stroke, are a major cause of long-term disability worldwide. Intracortical microstimulation (ICMS) can be used successfully to assist in guiding appropriate connections to restore lost sensorimotor integration. Activity-Dependent Stimulation (ADS) is a specific type of closed-loop ICMS that aims at coupling the activity of two different brain regions by stimulating one in response to activity in the other. Recently, ADS was used to effectively promote behavioral recovery in rodent models following a unilateral traumatic brain injury in the primary motor cortex. While behavioral benefits have been described, the neurophysiological changes in spared areas in response to this type of stimulation have not been fully characterized. Here we explored how single-unit spiking activity is impacted by a focal ischemic lesion and, subsequently, by an ADS treatment. Methods Intracortical microelectrode arrays were implanted in the ipsilesional rostral forelimb area (RFA) to record spike activity and to trigger intracortical microstimulation in the primary somatosensory area (S1) of anaesthetized Long Evans rats. An ischemic injury was induced in the caudal forelimb area through microinjections of Endothelin-1. Activity from both RFA and S1 was recorded and analyzed off-line by evaluating possible changes, either induced by the lesion in the Control group or by stimulation in the ADS group. Results We found that the ischemic lesion in the motor area led to an overall increase in spike activity within RFA and a decrease in S1 with respect to the baseline condition. Subsequent treatment with ADS increased the firing rate in both RFA and S1. Post-stimulation spiking activity was significantly higher compared to pre-stimulation activity in the ADS animals versus non-stimulated controls. Moreover, stimulation promoted the generation of highly synchronized bursting patterns in both RFA and S1 only in the ADS group. Conclusions This study describes the impact on single-unit activity in ipsilesional areas immediately following a cortical infarct and demonstrates that application of ADS is effective in altering this activity.

Abstract Background Transfemoral amputees experience a complex host of physical, psychological, and social challenges, compounded by the functional limitations of current transfemoral prostheses. However, the specific relationships between human factors and prosthesis design and performance characteristics have not yet been adequately investigated. The present study aims to address this knowledge gap. Methods A comprehensive single-cohort survey of 114 unilateral transfemoral amputees addressed a broad range of demographic and clinical characteristics, functional autonomy, satisfaction and attitudes towards their current prostheses, and design priorities for an ideal transfemoral prosthesis, including the possibility of active assistance from a robotic knee unit. The survey was custom-developed based on several standard questionnaires used to assess motor abilities and autonomy in activities of daily living, prosthesis satisfaction, and quality of life in lower-limb amputees. Survey data were analyzed to compare the experience (including autonomy and satisfaction) and design priorities of users of transfemoral prostheses with versus without microprocessor-controlled knee units (MPKs and NMPKs, respectively), with a subsequent analyses of cross-category correlation, principal component analysis (PCA), cost-sensitivity segmentation, and unsupervised K-means clustering applied within the most cost-sensitive participants, to identify functional groupings of users with respect to their design priorities. Results The cohort featured predominantly younger (

Integrated field and laboratory investigations, and numerical simulations of the 2019 paroxysmal explosions at Stromboli volcano revealed that they were anticipated by a week-to-month-long destabilization in the normal volcanic activity, a pattern common to all paroxysms.

Atrial fibrillation (AF) is common in patients with cardiac amyloidosis (CA) and is a significant risk factor for heart failure hospitalization and thromboembolic events. This study was designed to investigate the atrial electrofunctional predictors of incident AF in CA. A multicenter, observational study was conducted in 4 CA referral centers including sinus rhythm patients with light-chain (AL) and transthyretin (ATTR) CA undergoing electrocardiography and cardiac magnetic resonance imaging. The primary end point was new-onset AF occurrence. Overall, 96 patients (AL-CA, n = 40; ATTR-CA, n = 56) were enrolled. During an 18-month median follow-up (Q1–Q3, 7–29 months), 30 patients (29%) had incident AF. Compared with those without AF, patients with AF were older (79 vs 73 years; P =.001). They more frequently had ATTR (87% vs 45%; P <.001); electrocardiographic interatrial block (IAB), either partial (47% vs 21%; P =.011) or advanced (17% vs 3%; P =.017); and lower left atrial ejection fraction (LAEF; 29% vs 41%; P =.004). Age (hazard ratio [HR], 1.059; 95% CI, 1.002–1.118; P =.042), any type of IAB (HR, 2.211; 95% CI, 1.03–4.75; P =.041), and LAEF (HR, 0.967; 95% CI, 0.936–0.998; P =.044) emerged as independent predictors of incident AF. Patients exhibiting any type of IAB, LAEF <40%, and age >78 years showed a cumulative incidence for AF of 40% at 12 months. This risk was significantly higher than that carried by 1 (8.5%) or none (7.6%) of these 3 risk factors. In patients with CA, older age, IAB on 12-lead electrocardiography, and reduced LAEF on cardiac magnetic resonance imaging are significant and independent predictors of incident AF. A closer screening for AF is advisable in CA patients carrying these features. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Measles, mumps, and rubella (MMR) vaccines have been suggested as preventive measures to protect subjects from the worst sequelae of COVID-19 infection because neutralizing antibodies can cross-react with other viruses. Aim: To verify COVID-19 infection in MMR vaccinated and non-vaccinated healthcare workers and medical students in Trieste Hospitals. Results: Nurse aids resulted in significantly more infections than structured physicians (OR 1.80; 95% CI 1.14–2.80) while students resulted in less infections (OR, 0.66; 95% CI 0.43–1.01). The presence of an MMR vaccination was inversely associated with COVID-19 (OR, 0.77; 95% CI 0.61–0.96) but only in univariate analysis. In the multivariable logistic regression analysis, MMR vaccination lost statistical significance (OR, 0.86; 95%CI 0.62–1.20).On 13 HCWs hospitalized for COVID-19, 11 resulted not vaccinated for MMR. Discussion: Our study found a mild, non-significant reduction in SARS-CoV-2 infections in workers vaccinated with MMR.

Classifications of volcanic eruptions were first introduced in the early twentieth century mostly based on qualitative observations of eruptive activity, and over time, they have gradually been developed to incorporate more quantitative descriptions of the eruptive products from both deposits and observations of active volcanoes. Progress in physical volcanology, and increased capability in monitoring, measuring and modelling of explosive eruptions, has highlighted shortcomings in the way we classify eruptions and triggered a debate around the need for eruption classification and the advantages and disadvantages of existing classification schemes. Here, we (i) review and assess existing classification schemes, focussing on subaerial eruptions; (ii) summarize the fundamental processes that drive and parameters that characterize explosive volcanism; (iii) identify and prioritize the main research that will improve the understanding, characterization and classification of volcanic eruptions and (iv) provide a roadmap for producing a rational and comprehensive classification scheme. In particular, classification schemes need to be objective-driven and simple enough to permit scientific exchange and promote transfer of knowledge beyond the scientific community. Schemes should be comprehensive and encompass a variety of products, eruptive styles and processes, including for example, lava flows, pyroclastic density currents, gas emissions and cinder cone or caldera formation. Open questions, processes and parameters that need to be addressed and better characterized in order to develop more comprehensive classification schemes and to advance our understanding of volcanic eruptions include conduit processes and dynamics, abrupt transitions in eruption regime, unsteadiness, eruption energy and energy balance.

Postural control is a complex sensorimotor skill that is fundamental to our daily life. The abilities to maintain and recover balance degrade with age. However, the time decay of balance performance with age is not well understood. In this study, we aim at quantifying the age-dependent changes in standing balance under static and dynamic conditions. We tested 272 healthy subjects with ages ranging from 20 to 90. Subjects maintained the upright posture while standing on the robotic platform hunova®. In the evaluation of static balance, subjects stood on the fixed platform both with eyes open (EO) and eyes closed (EC). In the dynamic condition, subjects stood with eyes open on the moving foot platform that provided three different perturbations: (i) an inclination proportional to the center of pressure displacements, (ii) a pre-defined predictable motion, and (iii) an unpredictable and unexpected tilt. During all these tests, hunova® measured the inclination of the platform and the displacement of the center of pressure, while the trunk movements were recorded with an accelerometer placed on the sternum. To quantify balance performance, we computed spatio-temporal parameters typically used in clinical environments from the acceleration measures: mean velocity, variability of trunk motion, and trunk sway area. All subjects successfully completed all the proposed exercises. Their motor performance in the dynamic balance tasks quadratically changed with age. Also, we found that the reliance on visual feedback is not age-dependent in static conditions. All subjects well-tolerated the proposed protocol independently of their age without experiencing fatigue as we chose the timing of the evaluations based on clinical needs and routines. Thus, this study is a starting point for the definition of robot-based assessment protocols aiming at detecting the onset of age-related standing balance deficits and allowing the planning of tailored rehabilitation protocols to prevent falls in older adults.

One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the “biomarkers” that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the “Rehabilomics” has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.