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Advanced sensors/electrodes and signal processing techniques provide powerful tools to analyze surface electromyographic signals (sEMG) and their features, to decompose sEMG into the constituent motor unit action potential trains, and to identify synergies, neural muscle drive, and EEG–sEMG coherence. However, despite thousands of articles, dozens of textbooks, tutorials, consensus papers, and European and International efforts, the translation of this knowledge into clinical activities and assessment procedures has been very slow, likely because of lack of clinical studies and competent operators in the field. Understanding and using sEMG-based hardware and software tools requires a level of knowledge of signal processing and interpretation concepts that is multidisciplinary and is not provided by most academic curricula in physiotherapy, movement sciences, neurophysiology, rehabilitation, sport, and occupational medicine. The chasm existing between the available knowledge and its clinical applications in this field is discussed as well as the need for new clinical figures. The need for updating the training of physiotherapists, neurophysiology technicians, and clinical technologists is discussed as well as the required competences of trainers and trainees. Indications and examples are suggested and provide a basis for addressing the problem. Two teaching examples are provided in the Supplementary Material.

The motor features of people with cerebellar ataxia suggest that locomotion is substantially impaired due to incoordination of the head, trunk, and limbs. The purpose of this study was to investigate how well a wearable soft passive exoskeleton worked for motor coordination in these patients. We used an optoelectronic system to examine the gait of nine ataxic people in three different conditions: without an exoskeleton and with two variants of the exoskeleton, one less and the other more flexible. We investigated kinematics using trunk ranges of motion, the displacement of the center of mass in the medio-lateral direction, and the parameters of mechanical energy consumption and recovery. Furthermore, we investigated the lower limb and trunk muscle coactivation. The results revealed a reduction of the medio-lateral sway of the center of mass, a more efficient behavior of the body in the antero-posterior direction, an energy expenditure optimization, a reduction of muscle coactivation and a better coordination between muscle activations. As a result, the findings laid the groundwork for the device to be used in the rehabilitation of individuals with cerebellar ataxia. [ABSTRACT FROM AUTHOR]

In this study, we have analyzed the behavior of shear and compression forces at the L5-S1 joint during the execution of controlled lifting tasks designed on the basis of the revised NIOSH (National Institute for Occupational Safety and Health) lifting equation (RNLE) with an increasing lifting index (LI = 1, LI = 2, and LI = 3). We aim to verify the sensitivity of force indices with regard to risk levels. Twenty subjects performed the tasks, and the kinematic and kinetic data of their movement were acquired by using an optoelectronic motion analysis system and platform, respectively. Lumbosacral forces were calculated using the lower and upper body models, and some indices (i.e., maximum, medium, and range values) were extracted. Our findings confirm that the kinetic-based indices extracted from shear and compression forces at the L5-S1 joint are related to risk conditions, and they could improve the quantitative tools and machine-learning approaches that can also be used in a workspace to assess risk conditions during lifting tasks. [ABSTRACT FROM AUTHOR]

The interpretability of gait analysis studies in people with rare diseases, such as those with primary hereditary cerebellar ataxia (pwCA), is frequently limited by the small sample sizes and unbalanced datasets. The purpose of this study was to assess the effectiveness of data balancing and generative artificial intelligence (AI) algorithms in generating synthetic data reflecting the actual gait abnormalities of pwCA. Gait data of 30 pwCA (age: 51.6 ± 12.2 years; 13 females, 17 males) and 100 healthy subjects (age: 57.1 ± 10.4; 60 females, 40 males) were collected at the lumbar level with an inertial measurement unit. Subsampling, oversampling, synthetic minority oversampling, generative adversarial networks, and conditional tabular generative adversarial networks (ctGAN) were applied to generate datasets to be input to a random forest classifier. Consistency and explainability metrics were also calculated to assess the coherence of the generated dataset with known gait abnormalities of pwCA. ctGAN significantly improved the classification performance compared with the original dataset and traditional data augmentation methods. ctGAN are effective methods for balancing tabular datasets from populations with rare diseases, owing to their ability to improve diagnostic models with consistent explainability. [ABSTRACT FROM AUTHOR]

This editorial discusses the importance of job integration and reintegration for individuals with neuromuscular disorders and how advancements in technology can aid in this process. It emphasizes the need for rehabilitation, medical and surgical treatments, and ergonomic interventions to enable these individuals to fully benefit from vocational rehabilitation and overcome barriers to employment. The editorial also highlights the European Union's efforts to improve the social and economic status of persons with disabilities and the use of wearable monitoring sensors, feedback devices, exoskeletons, and collaborative robots in movement-related elements. The article proposes the use of a mobile collaborative robot with an interaction-assistive whole-body interface to help individuals who struggle with balance. [Extracted from the article]

Abstract Background Neuro-oncological population well expresses the complexity of neurological disability due to the multiple neurological deficits that affect these patients. Moreover, due to the therapeutical opportunities survival times for patients with brain tumor have increased and more of these patients require rehabilitation care. The figure of nurse in the interdisciplinary specialty of neurorehabilitation is not clearly defined, even if their role in this setting is recognized as being critical and is expanding. The purpose of the study is to identify the standard competencies for neurorehabilitation nurses that could be taught by means of a specialization course. Methods A literature review was conducted with preference given to works published between January 2000 and December 2008 in English. The search strategy identified 523 non-duplicated references of which 271 titles were considered relevant. After reviewing the abstracts, 147 papers were selected and made available to a group of healthcare professionals who were requested to classify them in few conceptual main areas defining the relative topics. Results The following five main areas were identified: clinical aspects of nursing; nursing techniques; nursing methodology; relational and organisational models; legal aspects of nursing. The relative topics were included within each area. As educational method a structured course based on lectures and practical sessions was designed. Also multi-choices questions were developed in order to evaluate the participants’ level of knowledge, while a semi-structured interview was prepared to investigate students’ satisfaction. Conclusions Literature shows that the development of rehabilitation depends on the improvement of scientific and practical knowledge of health care professionals. This structured training course could be incorporated into undergraduate nursing education programmes and also be inserted into continuing education programmes for graduate nurses. Developing expertise in neuro-rehabilitation for nurses, will be critical to improve overall care and care management of patients with highly complex disabilities as patients affected by brain tumors. The next step will be to start discussing, at the level of scientific societies linked to the field of neurorehabilitation and oncology, the development of a specialisation course in neurorehabilitation nursing.