1,720,993 research outputs found
LINarm: a low-cost variable stiffness device for upper-limb rehabilitation
No full textThis paper presents LINarm, a device for at-home robotic upper-limb neuro rehabilitation. Exploiting peculiar aspects of variable-stiffness actuators, it features functionalities widely addressed by devices specificall designed for assisted rehabilitation as controlled motion, force feedback and safety, together with the low-cost requirement for a wide spread installation at patients’ home
Analysis and synthesis of LinWWC-VSA, a Variable Stiffness Actuator for linear motion
No full textThis work presents the principle of operation of LinWWC-VSA, a Variable Stiffness Actuator (VSA) suitable to perform linear motions, conversely to the vast majority of VSAs typically designed to perform rotational movements and often affected by limits in the actually exploitable range of motions. It features two antagonist nonlinear equivalent springs, each of them made up of a cam wrapped by a wire and constrained by a torsion spring. This work presents methods both for the analysis and the synthesis of the actuator. Two synthesis methods, one numerical and one analytic, are described to design the cam profile as function of the desired stiffness-displacement characteristic of each equivalent nonlinear spring. The analytic method exploits the peculiar formulation of the logarithmic spiral. The theoretical aspects of the actuator are accompanied by numerical simulations
Biomechanical Assessments of the Upper Limb for Determining Fatigue, Strain and Effort from the Laboratory to the Industrial Working Place: A Systematic Review
Full text linkRecent human-centered developments in the industrial field (Industry 5.0) lead companies and stakeholders to ensure the wellbeing of their workers with assessments of upper limb performance in the workplace, with the aim of reducing work-related diseases and improving awareness of the physical status of workers, by assessing motor performance, fatigue, strain and effort. Such approaches are usually developed in laboratories and only at times they are translated to on-field applications; few studies summarized common practices for the assessments. Therefore, our aim is to review the current state-of-the-art approaches used for the assessment of fatigue, strain and effort in working scenarios and to analyze in detail the differences between studies that take place in the laboratory and in the workplace, in order to give insights on future trends and directions. A systematic review of the studies aimed at evaluating the motor performance, fatigue, strain and effort of the upper limb targeting working scenarios is presented. A total of 1375 articles were found in scientific databases and 288 were analyzed. About half of the scientific articles are focused on laboratory pilot studies investigating effort and fatigue in laboratories, while the other half are set in working places. Our results showed that assessing upper limb biomechanics is quite common in the field, but it is mostly performed with instrumental assessments in laboratory studies, while questionnaires and scales are preferred in working places. Future directions may be oriented towards multi-domain approaches able to exploit the potential of combined analyses, exploitation of instrumental approaches in workplace, targeting a wider range of people and implementing more structured trials to translate pilot studies to real practice
Design and testing of (A)MICO: a multimodal feedback system to facilitate the interaction between cobot and human operator
Full text linkThe present work describes the design, development and testing of a multimodal feedback system, named (A)MICO, with visual and acoustic feedback designed to facilitate the interaction of workers with collaborative robots (cobots) in production lines. The feedback is designed to make the human operator more aware of the cobot’s ongoing and future activities, and therefore gain more control over the situation. The ultimate goal is to obtain a new intuitive mode for transferring information through the combination of lights and sounds, not only to facilitate the flow of communication from the cobot to the operator, but also to make the interaction more accessible to neurodivergent groups, such as people with autism spectrum disorders. The design process focused on the evaluation of the human–robot interaction to select the situations where additional information is needed, and which is the best way to transfer messages as intuitively as possible. Potential end-users were actively involved during all stages of the design and development process. Five volunteers with high functioning autism participated in a preliminary co-design to identify the issues related to the interaction with the cobot and the logic of the multimodal signals. Then, to assess the system’s adaptability to several needs and the level of usability in providing information, validation tests were carried out involving a wider group of participants with ASD. The results suggest that the adoption of a multimodal communication strategy can be useful for making the workplace accessible and improving the well-being of all workers
A Planar Parallel Device for Neurorehabilitation
No full textThe patient population needing physical rehabilitation in the upper extremity is constantly increasing. Robotic devices have the potential to address this problem, however most of the rehabilitation robots are technically advanced and mainly designed for clinical use. This paper presents the development of an affordable device for upper-limb neurorehabilitation designed for home use. The device is based on a 2-DOF five-bar parallel kinematic mechanism. The prototype has been designed so that it can be bound on one side of a table with a clamp. A kinematic optimization was performed on the length of the links of the manipulator in order to provide the optimum kinematic behaviour within the desired workspace. The mechanical structure was developed, and a 3D-printed prototype was assembled. The prototype embeds two single-point load cells to measure the force exchanged with the patient. Rehabilitation-specific control algorithms are described and tested. Finally, an experimental procedure is performed in order to validate the accuracy of the position measurements. The assessment confirms an acceptable level of performance with respect to the requirements of the application under analysis
The effects of robotic assistance on upper limb spatial muscle synergies in healthy people during planar upper-limb training
Full text linkBACKGROUND: Robotic rehabilitation is a commonly adopted technique used to restore motor functionality of neurological patients. However, despite promising results were achieved, the effects of human-robot interaction on human motor control and the recovery mechanisms induced with robot assistance can be further investigated even on healthy subjects before translating to clinical practice. In this study, we adopt a standard paradigm for upper-limb rehabilitation (a planar device with assistive control) with linear and challenging curvilinear trajectories to investigate the effect of the assistance in human-robot interaction in healthy people. METHODS: Ten healthy subjects were instructed to perform a large set of radial and curvilinear movements in two interaction modes: 1) free movement (subjects hold the robot handle with no assistance) and 2) assisted movement (with a force tunnel assistance paradigm). Kinematics and EMGs from representative upper-limb muscles were recorded to extract phasic muscle synergies. The free and assisted interaction modes were compared assessing the level of assistance, error, and muscle synergy comparison between the two interaction modes. RESULTS: It was found that in free movement error magnitude is higher than with assistance, proving that task complexity required assistance also on healthy controls. Moreover, curvilinear tasks require more assistance than standard radial paths and error is higher. Interestingly, while assistance improved task performance, we found only a slight modification of phasic synergies when comparing assisted and free movement. CONCLUSIONS: We found that on healthy people, the effect of assistance was significant on task performance, but limited on muscle synergies. The findings of this study can find applications for assessing human-robot interaction and to design training to maximize motor recovery
A framework for human–robot collaboration enhanced by preference learning and ergonomics
Full text linkIndustry 5.0 aims to prioritize human operators, focusing on their well-being and capabilities, while promoting collaboration between humans and robots to enhance efficiency and productivity. The integration of collaborative robots must ensure the health and well-being of human operators. Indeed, this paper addresses the need for a human -centered framework proposing a preference -based optimization algorithm in a human- robot collaboration (HRC) scenario with an ergonomics assessment to improve working conditions. The HRC application consists of optimizing a collaborative robot end -effector pose during an object -handling task. The following approach (AmPL-RULA) utilizes an Active multi -Preference Learning (AmPL) algorithm, a preferencebased optimization method, where the user is requested to iteratively provide qualitative feedback by expressing pairwise preferences between a couple of candidates. To address physical well-being, an ergonomic performance index, Rapid Upper Limb Assessment (RULA), is combined with the user's pairwise preferences, so that the optimal setting can be computed. Experimental tests have been conducted to validate the method, involving collaborative assembly during the object handling performed by the robot. Results illustrate that the proposed method can improve the physical workload of the operator while easing the collaborative task
A Dataset on Human-Cobot Collaboration for Action Recognition in Manufacturing Assembly
No full textThis paper introduces a dataset on Human-cobot collaboration for Action Recognition in Manufacturing Assembly (HARMA3). It is a collection of RGB frames, Depth maps, RGB-to-depth-Aligned (RGB-A) frames and Skeleton data relative to actions performed by different subjects in collaboration with a cobot for building an Epicyclic Gear Train (EGT). In particular, 27 subjects executed several trials of the assembly task, which consisted of 7 actions. Data were collected in a laboratory scenario using two Microsoft® Azure Kinect cameras positioned in frontal and lateral positions. The dataset represents a good foundation for developing and testing advanced action recognition as well as action segmentation systems with far-reaching implications beyond human-cobot collaboration. Further potential applications include Computer Vision, Machine Learning, and Smart Manufacturing. Preliminary experiments for action segmentation by applying a state-of-the-art method on features extracted from RGB and skeletal data are presented in this paper, showing high-performance rates
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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