Modeling the Human Gait Phases by Using Bèzier Curves to Generate Walking Trajectories for Lower-Limb Exoskeletons.

The clinical usage of powered exoskeletons for the rehabilitation of patients affected by lower limb disorders has been constantly growing in the last decade. This paper presents a versatile and reliable gait pattern generator for these devices able to accommodate several gait requirements, i.e., step length, clearance, and time, and to suit a wide range of persons. In the proposed method, the human gait phases have been modeled with a set of trajectories as Bèzier curves, enabling a robotic lower-limb exoskeleton to walk in a continuous way, similarly to the physiological gait cycle. The kinematic, kinetic, and spatial requirements for each gait phase are translated into the control points of the Bèzier curves that define the trajectory for that phase. The outcome of this study has been tested on real scenarios with a group of healthy subjects wearing the TWIN lower-limb exoskeleton. They were asked to walk at different speeds, generally defined as slow, medium, and fast. The results are shown in terms of joint positions, velocities, and body-mass-normalized torques. The maximum hip and knee joint torque was observed in the support phase. While, at higher speeds the maximum hip torque was provided in the swing phase due to the mechanical properties and limits of the device. In terms of speed, all the subjects reached 0.44 m/s, which is the minimum required community ambulation.

Orientation Control System: Enhancing Aerial Maneuvers for Quadruped Robots.

For legged robots, aerial motions are the only option to overpass obstacles that cannot be circumvented with standard locomotion gaits. In these cases, the robot must perform a leap to either jump onto the obstacle or fly over it. However, these movements represent a challenge, because, during the flight phase, the Center of Mass (CoM) cannot be controlled, and there is limited controllability over the orientation of the robot. This paper focuses on the latter issue and proposes an Orientation Control System (OCS), consisting of two rotating and actuated masses (flywheels or reaction wheels), to gain control authority on the orientation of the robot. Due to the conservation of angular momentum, the rotational velocity if the robot can be adjusted to steer the robot's orientation, even when the robot has no contact with the ground. The axes of rotation of the flywheels are designed to be incident, leading to a compact orientation control system that is capable of controlling both roll and pitch angles, considering the different moments of inertia in the two directions. The concept was tested by means of simulations on the robot Solo12.

Meeting sustainable development goals via robotics and autonomous systems.

Robotics and autonomous systems are reshaping the world, changing healthcare, food production and biodiversity management. While they will play a fundamental role in delivering the UN Sustainable Development Goals, associated opportunities and threats are yet to be considered systematically. We report on a horizon scan evaluating robotics and autonomous systems impact on all Sustainable Development Goals, involving 102 experts from around the world. Robotics and autonomous systems are likely to transform how the Sustainable Development Goals are achieved, through replacing and supporting human activities, fostering innovation, enhancing remote access and improving monitoring. Emerging threats relate to reinforcing inequalities, exacerbating environmental change, diverting resources from tried-and-tested solutions and reducing freedom and privacy through inadequate governance. Although predicting future impacts of robotics and autonomous systems on the Sustainable Development Goals is difficult, thoroughly examining technological developments early is essential to prevent unintended detrimental consequences. Additionally, robotics and autonomous systems should be considered explicitly when developing future iterations of the Sustainable Development Goals to avoid reversing progress or exacerbating inequalities.

Influence of reduced muscle mass and quality on ventilator weaning and complications during intensive care unit stay in COVID-19 patients.

BACKGROUND & AIMS: Sarcopenia, a loss of muscle mass, quality and function, which is particularly evident in respiratory muscles, has been associated with many clinical adverse outcomes. In this study, we aimed at evaluating the role of reduced muscle mass and quality in predicting ventilation weaning, complications, length of intensive care unit (ICU) and of hospital stay and mortality in patients admitted to ICU for SARS-CoV-2-related pneumonia. METHODS: This was an observational study based on a review of medical records of all adult patients admitted to the ICU of a tertiary hospital in Milan and intubated for SARS-CoV-2-related pneumonia during the first wave of the COVID-19 pandemic. Muscle mass and quality measurement were retrieved from routine thoracic CT scans, when sections passing through the first, second or third lumbar vertebra were available. RESULTS: A total of 81 patients were enrolled. Muscle mass was associated with successful extubation (OR 1.02, 95% C.I. 1.00-1.03, p = 0.017), shorter ICU stay (OR 0.97, 95% C.I. 0.95-0.99, p = 0.03) and decreased hospital mortality (HR 0.98, 95% C.I. 0.96-0.99, p = 0.02). Muscle density was associated with successful extubation (OR 1.07, 95% C.I. 1.01-1.14; p = 0.02) and had an inverse association with the number of complications in ICU (Β -0.07, 95% C.I. -0.13 - -0.002, p = 0.03), length of hospitalization (Β -1.36, 95% C.I. -2.21 - -0.51, p = 0.002) and in-hospital mortality (HR 0.88, 95% C.I. 0.78-0.99, p = 0.046). CONCLUSIONS: Leveraging routine CT imaging to measure muscle mass and quality might constitute a simple, inexpensive and powerful tool to predict survival and disease course in patients with COVID-19. Preserving muscle mass during hospitalisation might have an adjuvant role in facilitating remission from COVID-19.

Residual lung damage following ARDS in COVID-19 ICU survivors.

BACKGROUND: Coronavirus disease 2019 acute respiratory distress syndrome (COVID-19 ARDS) is a disease that often requires invasive ventilation. Little is known about COVID-19 ARDS sequelae. We assessed the mid-term lung status of COVID-19 survivors and investigated factors associated with pulmonary sequelae. METHODS: All adult COVID-19 patients admitted to the intensive care unit from 25th February to 27th April 2020 were included. Lung function was evaluated through chest CT scan and pulmonary function tests (PFT). Logistic regression was used to identify predictors of persisting lung alterations. RESULTS: Forty-nine patients (75%) completed lung assessment. Chest CT scan was performed after a median (interquartile range) time of 97 (89-105) days, whilst PFT after 142 (133-160) days. The median age was 58 (52-65) years and most patients were male (90%). The median duration of mechanical ventilation was 11 (6-16) days. Median tidal volume/ideal body weight (TV/IBW) was 6.8 (5.71-7.67) ml/Kg. 59% and 63% of patients showed radiological and functional lung sequelae, respectively. The diffusion capacity of carbon monoxide (DLCO ) was reduced by 59%, with a median per cent of predicted DLCO of 72.1 (57.9-93.9) %. Mean TV/IBW during invasive ventilation emerged as an independent predictor of persistent CT scan abnormalities, whilst the duration of mechanical ventilation was an independent predictor of both CT and PFT abnormalities. The extension of lung involvement at hospital admission (evaluated through Radiographic Assessment of Lung Edema, RALE score) independently predicted the risk of persistent alterations in PFTs. CONCLUSIONS: Both the extent of lung parenchymal involvement and mechanical ventilation protocols predict morphological and functional lung abnormalities months after COVID-19.