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Objective: Spinal Muscular Atrophy (SMA) is a genetic neuromuscular disease affecting the lower motor neuron, carrying a significant burden on patients' general motor skills and quality of life, characterized by a great variability in phenotypic expression. As new therapeutic options make their appearance on the scene, sensitive clinical tools and outcome measures are needed, especially in adult patients undergoing treatment, in which the expected clinical response is a mild improvement or stabilization of disease progression., Methods: Here, we describe a new functional motor scale specifically designed for evaluating the endurance dimension for the upper and lower limbs in adult SMA patients., Results: The scale was first tested in eight control healthy subjects and then validated in ten adult SMA patients, proving intra- and inter-observer reliability. We also set up an evaluation protocol by using wearable devices including surface EMG and accelerometer., Conclusions: The endurance evaluation should integrate the standard clinical monitoring in the management and follow-up of SMA adult patients., Competing Interests: Authors have no conflict of interest to disclose., (©2023 Gaetano Conte Academy - Mediterranean Society of Myology, Naples, Italy.)

This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles. In the first part of the paper, we present a general taxonomy of the different defects that fall in two classes: visible (e.g., scratches, shape error, etc.) and palpable (e.g., crack, bump, etc.) defects. Then, we describe artificial visual processing techniques that are aimed at understanding of the captured scenery in a mathematical/logical way. We continue with a survey of textural defect detection based on statistical, structural and other approaches. Finally, we report the state of the art for approaching the detection and classification of defects through supervised and non-supervised classifiers and deep learning.

Generalization ability in tactile sensing for robotic manipulation is a prerequisite to effectively perform tasks in ever-changing environments. In particular, performing dynamic tactile perception is currently beyond the ability of robotic devices. A biomimetic approach to achieve this dexterity is to develop machines combining compliant robotic manipulators with neuroinspired architectures displaying computational adaptation. Here we demonstrate the feasibility of this approach for dynamic touch tasks experimented by integrating our sensing apparatus in a 6 degrees of freedom robotic arm via a soft wrist. We embodied in the system a model of spike-based neuromorphic encoding of tactile stimuli, emulating the discrimination properties of cuneate nucleus neurons based on pathways with differential delay lines. These strategies allowed the system to correctly perform a dynamic touch protocol of edge orientation recognition (ridges from 0 to 40°, with a step of 5°). Crucially, the task was robust to contact noise and was performed with high performance irrespectively of sensing conditions (sensing forces and velocities). These results are a step forward toward the development of robotic arms able to physically interact in real-world environments with tactile sensing.

The role of the mechanical properties of the neuromuscular system in motor control has been investigated for a long time in both human and animal subjects, mainly through the application of mechanical perturbations to the limb during natural movements and the observation of its corrective responses. These methods have provided a wealth of insight into how the central nervous system controls the limb. They suffer, however, from the fact that it is almost impossible to separate the active and passive components of the measured arm stiffness and that the measurement may themselves alter the stiffness characteristic of the arm. As a complement to these analyses, the implementation of a given neuroscientific hypothesis on a real mechanical system could overcome these measurement artifact and provide a tool that is, under full control of the experimenter, able to replicate the relevant functional features of the human arm. In this article, we introduce the NEURARM platform, a robotic arm intended to test hypotheses on the human motor control system. As such, NEURARM satisfies two key requirements. First, its kinematic parameters and inertia are similar to that of the human arm. Second, NEURARM mimics the main physical features of the human actuation system, specifically, the use of tendons to transfer force, the presence of antagonistic muscle pairs, the passive elasticity of muscles in the absence of any neural feedback and the non-linear elastic behaviour. This article presents the design and characterization of the NEURARM actuation system. The resulting mechanical behaviour, which has been tested in joint and Cartesian space under static and dynamic conditions, proves that the NEURARM platform can be exploited as a robotic model of the human arm, and could thus represent a powerful tool for neuroscience investigations.

This work describes the neuro-robotics paradigm: the fusion of neuroscience and robotics. The fusion of neuroscience and robotics, called neuro-robotics, is fundamental to develop robotic systems to be used in functional support, personal assistance and neuro-rehabilitation. While usually the robotic device is considered as a "tool" for neuroscientific studies, a breakthrough is obtained if the two scientific competences and methodologies converge to develop innovative platforms to go beyond robotics by including novel models to design better robots. This paper describes three robotic platforms developed at the ARTS lab of Scuola Superiore Sant'Anna, implementing neuro-robotic design paradigm.

It has been concluded from numerous neurophysiological studies that humans rely on detecting discrete mechanical events that occur when grasping, lifting and replacing an object, i.e., during a prototypical manipulation task. Such events represent transitions between phases of the evolving manipulation task such as object contact, lift-off, etc., and appear to provide critical information required for the sequential control of the task as well as for corrections and parameterization of the task. We have sensorized a biomechatronic anthropomorphic hand with the goal to detect such mechanical transients. The developed sensors were designed to specifically provide the information about task-relevant discrete events rather than to mimic their biological counterparts. To accomplish this we have developed (1) a contact sensor that can be applied to the surface of the robotic fingers and that show a sensitivity to indentation and a spatial resolution comparable to that of the human glabrous skin, and (2) a sensitive low-noise three-axial force sensor that was embedded in the robotic fingertips and showed a frequency response covering the range observed in biological tactile sensors. We describe the design and fabrication of these sensors, their sensory properties and show representative recordings from the sensors during grasp-and-lift tasks. We show how the combined use of the two sensors is able to provide information about crucial mechanical events during such tasks. We discuss the importance of the sensorized hand as a test bed for low-level grasp controllers and for the development of functional sensory feedback from prosthetic devices.

Home care is greatly expanding because of the savings it offers by avoiding unnecessary hospitalization and also because patients benefit from being in their own home environments. Since 1988, Societa Assistenza Malato Oncologico Terminale (SAMOT) has organized a pain relief and home palliative care unit for terminal cancer patients. Objectives, difficulties, protocols, and achievements of 4 years of experience were examined, and the findings of the various years were compared. Our results suggest that considerable progress has been made in home palliative care. There are still social and cultural difficulties to overcome, however.

Analgesic response, incidental pain and pain mechanism were evaluated in order to predict the chances of pain relief in advanced cancer patients. In an observation period of about 2 months, 130 patients were followed at home until death using only a pharmacological approach to control pain according to the WHO ladders. Ninety-eight patients were considered. Pain relief was considered good if less than moderate. Pain was assessed during the course of examinations (2-3 a week) by independent observers. If other techniques were needed the result was considered negative. The patients were tested with an NSAID (Diclofenac) and assigned to group 1 if the pain became slight in 3 days. If the response was negative, a 4-day trial with opioids was started. If the pain was slight the patient was included in group 3, otherwise in group 5. Every patient belonging to these groups but with incidentical pain was included in groups 2, 4 and 6, respectively. For each group a subdivision was made according to the pain characteristics. There was a progressive worsening in pain relief in groups 4, 5 and 6, suggesting a good correlation between response to the drugs and future chances of pain control in a period of 2 months. This study demonstrates that incidental pain reduces the possibility of pain control (50%) with the exclusive administration of analgesics in patients with a mean life expectation of about 2 months. This negative influence is counterbalanced by the possible individual response to analgesics administered sequentially during a 1-week period (85.8% good pain relief with NSAID, 74% with opioids).(ABSTRACT TRUNCATED AT 250 WORDS)