Mechanical lifting energy consumption in work activities designed by means of the "revised NIOSH lifting equation"\u80\u9d

The aims of the present work were: to calculate lifting energy consumption (LEC) in work activities designed to have a growing lifting index (LI) by means of revised NIOSH lifting equation; to evaluate the relationship between LEC and forces at the L5-S1 joint. The kinematic and kinetic data of 20 workers were recorded during the execution of lifting tasks in three conditions. We computed kinetic, potential and mechanical energy and the corresponding LEC by considering three different centers of mass of: 1) the load (CoML); 2) the multi-segment upper body model and load together (CoMUpp+L); 3) the whole body and load together (CoMTot). We also estimated compression and shear forces. Results shows that LEC calculated for CoMUpp+L and CoMTot grew significantly with the LI and that all the lifting condition pairs are discriminated. The correlation analysis highlighted a relationship between LEC and forces that determine injuries at the L5-S1 joint

Constrained wiki: the Wikiway to validating content

The "WikiWay" is the open editing philosophy of wikis meant to foster open collaboration and continuous improvement of their content. Just like other online communities, wikis often introduce and enforce conventions, constraints, and rules for their content, but do so in a considerably softer way, expecting authors to deliver content that satisfies the conventions and the constraints, or, failing that, having volunteers of the community, the WikiGnomes, fix others' content accordingly. Constrained wikis is our generic framework for wikis to implement validators of community-specific constraints and conventions that preserve the WikiWay and their open collaboration features. To this end, specific requirements need to be observed by validators and a specific software architecture can be used for their implementation, that is, as independent functions (implemented as internal modules or external services) used in a nonintrusive way. Two separate proof-of-concept validators have been implemented for MediaWiki and MoinMoin, respectively, providing an annotated view functions, that is, presenting content authors with violation warnings, rather than preventing them from saving a noncompliant text

Characterizing the Gait of People With Different Types of Amputation and Prosthetic Components Through Multimodal Measurements: A Methodological Perspective

Prosthetic gait implies the use of compensatory motor strategies, including alterations in gait biomechanics and adaptations in the neural control mechanisms adopted by the central nervous system. Despite the constant technological advancements in prostheses design that led to a reduction in compensatory movements and an increased acceptance by the users, a deep comprehension of the numerous factors that influence prosthetic gait is still needed. The quantitative prosthetic gait analysis is an essential step in the development of new and ergonomic devices and to optimize the rehabilitation therapies. Nevertheless, the assessment of prosthetic gait is still carried out by a heterogeneous variety of methodologies, and this limits the comparison of results from different studies, complicating the definition of shared and well-accepted guidelines among clinicians, therapists, physicians, and engineers. This perspective article starts from the results of a project funded by the Italian Worker's Compensation Authority (INAIL) that led to the generation of an extended dataset of measurements involving kinematic, kinetic, and electrophysiological recordings in subjects with different types of amputation and prosthetic components. By encompassing different studies published along the project activities, we discuss the specific information that can be extracted by different kinds of measurements, and we here provide a methodological perspective related to multimodal prosthetic gait assessment, highlighting how, for designing improved prostheses and more effective therapies for patients, it is of critical importance to analyze movement neural control and its mechanical actuation as a whole, without limiting the focus to one specific aspect

Bio-Cooperative Approach for the Human-in-the-Loop Control of an End-Effector Rehabilitation Robot

The design of patient-tailored rehabilitative protocols represents one of the crucial factors that influence motor recovery mechanisms, such as neuroplasticity. This approach, including the patient in the control loop and characterized by a control strategy adaptable to the user's requirements, is expected to significantly improve functional recovery in robot-aided rehabilitation. In this paper, a novel 3D bio-cooperative robotic platform is developed. A new arm-weight support system is included into an operational robotic platform for 3D upper limb robot-aided rehabilitation. The robotic platform is capable of adapting therapy characteristics to specific patient needs, thanks to biomechanical and physiological measurements, and thus closing the subject in the control loop. The level of arm-weight support and the level of the assistance provided by the end-effector robot are varied on the basis of muscular fatigue and biomechanical indicators. An assistance-as-needed approach is applied to provide the appropriate amount of assistance. The proposed platform has been experimentally validated on 10 healthy subjects; they performed 3D point-to-point tasks in two different conditions, i.e., with and without assistance-as-needed. The results have demonstrated the capability of the proposed system to properly adapt to real needs of the patients. Moreover, the provided assistance was shown to reduce the muscular fatigue without negatively influencing motion execution

Robot-assisted upper limb training for patients with multiple sclerosis: an evidence-based review of clinical applications and effectiveness

Upper extremities limitation is a common functional impairment in patients with Multiple Sclerosis (PwMS). Novel technological devices are increasingly used in neurorehabilitation to support motor function improvement and the quantitative assessment of motor performance during training in patients with neurological diseases. In this review, we systematically report the evidence on clinical applications and robotic-assisted arm training (RAT) in functional recovery in PwMS. PubMed/MEDLINE, the Cochrane Library, and the Physiotherapy Evidence Database (PEDro) databases were systematically searched from inception to March 2021. The 10-item PEDro scale assessed the study quality for the RCT, and the AMSTAR-2 was used to assess the quality of the systematic review. The 5-item Oxford CEBM scale was used to rate the level of evidence. A total of 10 studies (161 subjects) were included. The selected studies included one systematic review, four RCTs, one randomized crossover, and four case series. The RCTs were scored as high-quality studies, while the systematic review was determined to be of low quality. Shoulder range of motion, handgrip strength, and proximal arm impairment improved after RAT. Manual dexterity, arm function, and use in daily life also ameliorated arm function. The high clinical heterogeneity of treatment programs and the variety of robot devices affects the generalizability of the study results; therefore, we emphasize the need to standardize the intervention type in future studies that evaluate the role of robotic-assisted training in PwMS. Robot-assisted treatment seems safe and useful to increase manual dexterity and the quality of movement execution in PwMS with moderate to severe disability. Additional studies with an adequate sample size and methodological rigour are warranted to drive definite conclusion

Electromechanical and robotic devices for gait and balance rehabilitation of children with neurological disability: a systematic review

In the last two decades, a growing interest has been focused on gait and balance robot-assisted rehabilitation in children with neurological disabilities. Robotic devices allow the implementation of intensive, task-specific training fostering functional recovery and neuroplasticity phenomena. However, limited attention has been paid to the protocols used in this research framework. This systematic review aims to provide an overview of the existing literature on robotic systems for the rehabilitation of gait and balance in children with neurological disabilities and their rehabilitation applications. The literature search was carried out independently and synchronously by three authors on the following databases: MEDLINE, Cochrane Library, PeDro, Institute of Electrical and Electronics Engineers, ScienceDirect, and Google Scholar. The data collected included three subsections referring to clinical, technical, and regulatory aspects. Thirty-one articles out of 81 found on the primary literature search were included in the systematic review. Most studies involved children with cerebral palsy. Only one-third of the studies were randomized controlled trials. Overall, 17 devices (nine end-effector systems and eight exoskeletons) were investigated, among which only 4 (24%) were bore the CE mark. Studies differ on rehabilitation protocols duration, intensity, and outcome measures. Future research should improve both rehabilitation protocols\u2019 and devices\u2019 descriptions

Upper limb robotic rehabilitation for patients with cervical spinal cord injury: a comprehensive review

The upper extremities limitation represents one of the essential functional impairments in patients with cervical spinal cord injury. Electromechanics assisted devices and robots are increasingly used in neurorehabilitation to help functional improvement in patients with neurological diseases. This review aimed to systematically report the evidence-based, state-of-art on clinical applications and robotic-assisted arm training (RAT) in motor and functional recovery in subjects affected by cervical spinal cord injury. The present study has been carried out within the framework of the Italian Consensus Conference on "Rehabilitation assisted by robotic and electromechanical devices for persons with disability of neurological origin" (CICERONE). PubMed/MEDLINE, Cochrane Library, and Physiotherapy Evidence Database (PEDro) databases were systematically searched from inception to September 2021. The 10-item PEDro scale assessed the study quality for the RCT and the AMSTAR-2 for the systematic review. Two different authors rated the studies included in this review. If consensus was not achieved after discussion, a third reviewer was interrogated. The five-item Oxford CEBM scale was used to rate the level of evidence. A total of 11 studies were included. The selected studies were: two systematic reviews, two RCTs, one parallel-group controlled trial, one longitudinal intervention study and five case series. One RCT was scored as a high-quality study, while the systematic review was of low quality. RAT was reported as feasible and safe. Initial positive effects of RAT were found for arm function and quality of movement in addition to conventional therapy. The high clinical heterogeneity of treatment programs and the variety of robot devices could severely affect the generalizability of the study results. Therefore, future studies are warranted to standardize the type of intervention and evaluate the role of robotic-assisted training in subjects affected by cervical spinal cord injury

Effects of robotic upper limb treatment after stroke on cognitive patterns: A systematic review

Background: Robotic therapy (RT) has been internationally recognized for the motor rehabilitation of the upper limb. Although it seems that RT can stimulate and promote neuroplasticity, the effectiveness of robotics in restoring cognitive deficits has been considered only in a few recent studies. Objective: To verify whether, in the current state of the literature, cognitive measures are used as inclusion or exclusion criteria and/or outcomes measures in robotic upper limb rehabilitation in stroke patients. Methods: The systematic review was conducted according to PRISMA guidelines. Studies eligible were identified through PubMed/MEDLINE and Web of Science from inception to March 2021. Results: Eighty-one studies were considered in this systematic review. Seventy-three studies have at least a cognitive inclusion or exclusion criteria, while only seven studies assessed cognitive outcomes. Conclusion: Despite the high presence of cognitive instruments used for inclusion/exclusion criteria their heterogeneity did not allow the identification of a guideline for the evaluation of patients in different stroke stages. Therefore, although the heterogeneity and the low percentage of studies that included cognitive outcomes, seemed that the latter were positively influenced by RT in post-stroke rehabilitation. Future larger RCTs are needed to outline which cognitive scales are most suitable and their cut-off, as well as what cognitive outcome measures to use in the various stages of post-stroke rehabilitation

Frame-driven Extraction of Linked Data and Ontologies from Text

Ontology design and population -core aspects of semantic technologies- re- cently have become fields of great interest due to the increasing need of domain-specific knowledge bases that can boost the use of Semantic Web. For building such knowledge resources, the state of the art tools for ontology design require a lot of human work. Producing meaningful schemas and populating them with domain-specific data is in fact a very difficult and time-consuming task. Even more if the task consists in modelling knowledge at a web scale. The primary aim of this work is to investigate a novel and flexible method- ology for automatically learning ontology from textual data, lightening the human workload required for conceptualizing domain-specific knowledge and populating an extracted schema with real data, speeding up the whole ontology production process. Here computational linguistics plays a fundamental role, from automati- cally identifying facts from natural language and extracting frame of relations among recognized entities, to producing linked data with which extending existing knowledge bases or creating new ones. In the state of the art, automatic ontology learning systems are mainly based on plain-pipelined linguistics classifiers performing tasks such as Named Entity recognition, Entity resolution, Taxonomy and Relation extraction [11]. These approaches present some weaknesses, specially in capturing struc- tures through which the meaning of complex concepts is expressed [24]. Humans, in fact, tend to organize knowledge in well-defined patterns, which include participant entities and meaningful relations linking entities with each other. In literature, these structures have been called Semantic Frames by Fill- 6 Introduction more [20], or more recently as Knowledge Patterns [23]. Some NLP studies has recently shown the possibility of performing more accurate deep parsing with the ability of logically understanding the structure of discourse [7]. In this work, some of these technologies have been investigated and em- ployed to produce accurate ontology schemas. The long-term goal is to collect large amounts of semantically structured information from the web of crowds, through an automated process, in order to identify and investigate the cognitive patterns used by human to organize their knowledge

Design in laboratorio: analisi multifattoriali del movimento di un operatore al banco cassa.

Lo sviluppo di un prodotto richiede in genere, con riferimenti ai bisogni dell\u2019utente, il coinvolgimento attivo di una serie di figure professionali in relazione alle caratteristiche e alla complessit\ue0 del prodotto stesso. Questa necessit\ue0 si presenta anche per lo sviluppo di un nuovo \u201cconcept\u201d di banco cassa. I vari elementi coinvolti nello sviluppo di un banco cassa, richiedono una attenta analisi multifattoriale, che deve risolvere vari aspetti