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BACKGROUND: Ultrasound-guided galvanic electrolysis technique (USGET) is an innovative mini-invasive intervention with the potential to optimise outcomes in the treatment of Achille's tendinopathy (AT). OBJECTIVE: The aim of this pilot study is to evaluate the efficacy of adding USGET to conventional eccentric exercise treatment in patients with chronic AT. METHODS: Inclusion criteria were patients with unilateral non-insertional AT, pain lasting > 3 months, aged 25–60 years. Patients were randomised in two groups receiving the same physiotherapy treatment (2 sessions per week for 8 weeks). In addition, the experimental group received three USGET stimulations, one every 15 days. Outcome measures were assessment of Achilles tendinopathy severity using the Victorian Institute of Sport Assessment-Achilles (VISA-A) and pain intensity using the Visual Analogue Scale (VAS). Assessment points occurred at the onset of treatment (T0), its conclusion (T1), and subsequent follow-ups at one (T2) and two months (T3). RESULTS: Out of the 52 patients who met the study inclusion criteria, two participants withdrew from the study, resulting in a total of 50 subjects who completed the research. None of the parameters showed a different distribution at T1 (p > 0.337). At T2, there was a statistical difference in VISA-A (p = 0.010) and its subscales and VAS (p = 0.002) in the USGET group. At T3, both groups improved with a statistical difference observed in VISA-A (p < 0.001) and its subscales Pain (p = 0.004), Function (p = 0.003) and Sport (p = 0.002), but the EG patients showed a greater improvement. No adverse events were reported. CONCLUSION: The effect of USGET combined with eccentric exercise appears to be a safe and effective technique for achieving pain relief and functional recovery in the medium term, supporting the integrated use of USGET as a rehabilitative treatment option for patients with chronic AT. [ABSTRACT FROM AUTHOR]

According to the modular hypothesis for the control of movement, muscles are recruited in synergies, which capture muscle coordination in space, time, or both. In the last two decades, muscle synergy analysis has become a well-established framework in the motor control field and for the characterization of motor impairments in neurological patients. Altered modular control during a locomotion task has been often proposed as a potential quantitative metric for characterizing pathological conditions. Therefore, the purpose of this systematic review is to analyze the recent literature that used a muscle synergy analysis of neurological patients' locomotion as an indicator of motor rehabilitation therapy effectiveness, encompassing the key methodological elements to date. Searches for the relevant literature were made in Web of Science, PubMed, and Scopus. Most of the 15 full-text articles which were retrieved and included in this review identified an effect of the rehabilitation intervention on muscle synergies. However, the used experimental and methodological approaches varied across studies. Despite the scarcity of studies that investigated the effect of rehabilitation on muscle synergies, this review supports the utility of muscle synergies as a marker of the effectiveness of rehabilitative therapy and highlights the challenges and open issues that future works need to address to introduce the muscle synergies in the clinical practice and decisional process. [ABSTRACT FROM AUTHOR]

The central nervous system (CNS) may produce the same endpoint trajectory or torque profile with different muscle activation patterns. What differentiates these patterns is the presence of cocontraction, which does not contribute to effective torque generation but allows to modulate joints' mechanical stiffness. Although it has been suggested that the generation of force and the modulation of stiffness rely on separate pathways, a characterization of the differences between the synaptic inputs to motor neurons (MNs) underlying these tasks is still missing. In this study, participants coactivated the same pair of upper-limb muscles, i.e., the biceps brachii and the triceps brachii, to perform two functionally different tasks: limb stiffness modulation or endpoint force generation. Spike trains of MNs were identified through decomposition of high-density electromyograms (EMGs) collected from the two muscles. Cross-correlogram showed a higher synchronization between MNs recruited to modulate stiffness, whereas cross-muscle coherence analysis revealed peaks in the β-band, which is commonly ascribed to a cortical origin. These peaks did not appear during the coactivation for force generation, thus suggesting separate cortical inputs for stiffness modulation. Moreover, a within-muscle coherence analysis identified two subsets of MNs that were selectively recruited to generate force or regulate stiffness. This study is the first to highlight different characteristics, and probable different neural origins, of the synaptic inputs driving a pair of muscles under different functional conditions. We suggest that stiffness modulation is driven by cortical inputs that project to a separate set of MNs, supporting the existence of a separate pathway underlying the control of stiffness. NEW & NOTEWORTHY: The characterization of the pathways underlying force generation or stiffness modulation are still unknown. In this study, we demonstrated that the common input to motor neurons of antagonist muscles shows a high-frequency component when muscles are coactivated to modulate stiffness but not to generate force. Our results provide novel insights on the neural strategies for the recruitment of multiple muscles by identifying specific spectral characteristics of the synaptic inputs underlying functionally different tasks. [ABSTRACT FROM AUTHOR]

The impact of COVID-19 on sport and physical activity has been a subject of considerable interest and concern. Padel satisfies the desire for social interaction and a return to sport after a period of inactivity. The aim of this study is to show a correlation between return to sport and related injuries in a population of padel players. The study was carried out in a survey mode, consisting of a questionnaire with four sections and fifty questions on the biographical data of the individual, lifestyle before and after the pandemic, knowledge and playing level of padel and injuries. The self-administered online questionnaire was developed and validated by a panel of physiotherapists, orthopaedic surgeons, and physiatrists with experience in clinical practice and/or musculoskeletal research. The study was conducted in a survey mode from a smartphone or computer via a link to a multiple-choice document. The link to the questionnaire was distributed via mailing lists, social media, and chat applications. A previous history of injury prior to the Covid pandemic, a higher body mass index, and increased sporting activity were all linked to a higher number of injuries. Daily steps, age, experience, and the average number of games per week were all found to have no significant effect. The enforced rest during the lockdown period highlighted the importance of comprehensive injury prevention strategies in sports, as well as understanding the impact of de-training and periods of inactivity on risk of injury. [ABSTRACT FROM AUTHOR]

Estimation of the force exerted by muscles from their electromyographic (EMG) activity may be useful to control robotic devices. Approximating end-point forces as a linear combination of the activities of multiple muscles acting on a limb may lead to an inaccurate estimation because of the dependency between the EMG signals, i.e., multi-collinearity. This study compared the EMG-to-force mapping estimation performed with standard multiple linear regression and with three other algorithms designed to reduce different sources of the detrimental effects of multi-collinearity: Ridge Regression, which performs an L2 regularization through a penalty term; linear regression with constraints from foreknown anatomical boundaries, derived from a musculoskeletal model; linear regression of a reduced number of muscular degrees of freedom through the identification of muscle synergies. Two datasets, both collected during the exertion of submaximal isometric forces along multiple directions with the upper limb, were exploited. One included data collected across five sessions and the other during the simultaneous exertion of force and generation of different levels of co-contraction. The accuracy and consistency of the EMG-to-force mappings were assessed to determine the strengths and drawbacks of each algorithm. When applied to multiple sessions, Ridge Regression achieved higher accuracy (R2 = 0.70) but estimations based on muscle synergies were more consistent (differences between the pulling vectors of mappings extracted from different sessions: 67%). In contrast, the implementation of anatomical constraints was the best solution, both in terms of consistency (R2 = 0.64) and accuracy (74%), in the case of different co-contraction conditions. These results may be used for the selection of the mapping between EMG and force to be implemented in myoelectrically controlled robotic devices. [ABSTRACT FROM AUTHOR]

In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The "virtual stiffness" method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations. [ABSTRACT FROM AUTHOR]

Stroke is the second cause of disability and death worldwide, highly impacting patient's quality of life. Several changes in brain architecture and function led by stroke can be disclosed by neurophysiological techniques. Specifically, electroencephalogram (EEG) can disclose brain oscillatory rhythms, which can be considered as a possible outcome measure for stroke recovery, and potentially shaped by neuromodulation techniques. We performed a review of randomized controlled trials on the role of brain oscillations in patients with post-stroke searching the following databases: Pubmed, Scopus, and the Web of Science, from 2012 to 2022. Thirteen studies involving 346 patients in total were included. Patients in the control groups received various treatments (sham or different stimulation modalities) in different post-stroke phases. This review describes the state of the art in the existing randomized controlled trials evaluating post-stroke motor function recovery after conventional rehabilitation treatment associated with neuromodulation techniques. Moreover, the role of brain pattern rhythms to modulate cortical excitability has been analyzed. To date, neuromodulation approaches could be considered a valid tool to improve stroke rehabilitation outcomes, despite more high-quality, and homogeneous randomized clinical trials are needed to determine to which extent motor functional impairment after stroke can be improved by neuromodulation approaches and which one could provide better functional outcomes. However, the high reproducibility of brain oscillatory rhythms could be considered a promising predictive outcome measure applicable to evaluate patients with stroke recovery after rehabilitation. [ABSTRACT FROM AUTHOR]

Assessing maximum voluntary bite force is important to characterize the functional state of the masticatory system. Due to several factors affecting the estimation of the maximum bite force, a unique solution combining desirable features such as reliability, accuracy, precision, usability, and comfort is not available. The aim of the present study was to develop a low-cost bite force measurement device allowing for subject-specific customization, comfortable bite force expression, and reliable force estimation over time. The device was realized using an inexpensive load cell, two 3D printed ergonomic forks hosting reusable subject-specific silicone molds, a read-out system based on a low-cost microcontroller, and a wireless link to a personal computer. A simple model was used to estimate bite force taking into account individual morphology and device placement in the mouth. Measurement reliability, accuracy, and precision were assessed on a calibration dataset. A validation procedure on healthy participants was performed to assess the repeatability of the measurements over multiple repetitions and sessions. A 2% precision and 2% accuracy were achieved on measurements of forces in the physiological range of adult bite forces. Multiple recordings on healthy participants demonstrated good repeatability (coefficient of variation 11%) with no significant effect of repetition and session. The novel device provides an affordable and reliable solution for assessing maximum bite force that can be easily used to perform clinical evaluations in single sessions or in longitudinal studies. [ABSTRACT FROM AUTHOR]

Humans have a remarkable capacity to learn new motor skills, a process that requires novel muscle activity patterns. Muscle synergies may simplify the generation of muscle patterns through the selection of a small number of synergy combinations. Learning of new motor skills may then be achieved by acquiring novel muscle synergies. In a previous study, we used myoelectric control to construct virtual surgeries that altered the mapping from muscle activity to cursor movements. After compatible virtual surgeries, which could be compensated by recombining subject-specific muscle synergies, participants adapted quickly. In contrast, after incompatible virtual surgeries, which could not be compensated by recombining existing synergies, participants explored new muscle patterns but failed to adapt. Here, we tested whether task space exploration can promote learning of novel muscle synergies required to overcome an incompatible surgery. Participants performed the same reaching task as in our previous study but with more time to complete each trial, thus allowing for exploration. We found an improvement in trial success after incompatible virtual surgeries. Remarkably, improvements in movement direction accuracy after incompatible surgeries occurred faster for corrective movements than for the initial movement, suggesting that learning of new synergies is more effective when used for feedback control. Moreover, reaction time was significantly higher after incompatible than compatible virtual surgeries, suggesting an increased use of an explicit adaptive strategy to overcome incompatible surgeries. Taken together, these results indicate that exploration is important for skill learning and suggest that human participants, with sufficient time, can learn new muscle synergies. NEW & NOTEWORTHY Motor skill learning requires the acquisition of novel muscle patterns, a slow adaptive process. Here we show that learning to control a cursor after an incompatible virtual surgery, a complex skill requiring new muscle synergies, is possible when enough time for task space exploration is provided. Our results suggest that learning new synergies is related to the exceptional human capacity to acquire a wide variety of novel motor skills with practice. [ABSTRACT FROM AUTHOR]

Background: Periodic quality control (QC) procedures are important in order to guarantee the image quality of radiological equipment and are also conducted using phantoms simulating human body. Objective: To perform (QC) measurements in intraoral imaging devices, a new and simple phantom was manufactured. Besides, to simplify QC procedures, computerized LabView-based software has been devised, enabling determination of image quantitative parameters in real time or during post processing. Material and Methods: In this experimental study, the novel developed phantom consists of a Polymethyl methacrylate (PMMA) circular insert. It is able to perform a complete QC image program of X-ray intraoral equipment and also causes the evaluation of image uniformity, high and low contrast spatial resolution, image linearity and artefacts, with only two exposures. Results: Three raters analyzed the images using the LabView dedicated software and determined the quantitative and qualitative parameters in an innovative and accurate way. Statistical analysis evaluated the reliability of this study. Good accuracy of the quantitative and qualitative measurements for the different intraoral systems was obtained and no statistical differences were found using the inter-rater analysis. Conclusion: The achieved results and the related statistical analysis showed the validity of this methodology, which could be proposed as an alternative to the commonly adopted procedures, and suggested that the novel phantom, coupled with the LabView based software, could be considered as an effective tool to carry out a QC image program in a reproducible manner. [ABSTRACT FROM AUTHOR]

Manipulative actions involving unstable interactions with the environment require controlling mechanical impedance through muscle co-contraction. While much research has focused on how the central nervous system (CNS) selects the muscle patterns underlying a desired movement or end-point force, the coordination strategies used to achieve a desired end-point impedance have received considerably less attention. We recorded isometric forces at the hand and electromyographic (EMG) signals in subjects performing a reaching task with an external disturbance. In a virtual environment, subjects displaced a cursor by applying isometric forces and were instructed to reach targets in 20 spatial locations. The motion of the cursor was then perturbed by disturbances whose effects could be attenuated by increasing co-contraction. All subjects could voluntarily modulate co-contraction when disturbances of different magnitudes were applied. For most muscles, activation was modulated by target direction according to a cosine tuning function with an offset and an amplitude increasing with disturbance magnitude. Co-contraction was characterized by projecting the muscle activation vector onto the null space of the EMG-to-force mapping. Even in the baseline the magnitude of the null space projection was larger than the minimum magnitude required for non-negative muscle activations. Moreover, the increase in co-contraction was not obtained by scaling the baseline null space projection, scaling the difference between the null space projections in any block and the projection of the non-negative minimum-norm muscle vector, or scaling the difference between the null space projections in the perturbed blocks and the baseline null space projection. However, the null space projections in the perturbed blocks were obtained by linear combination of the baseline null space projection and the muscle activation used to increase co-contraction without generating any force. The failure of scaling rules in explaining voluntary modulation of arm co-contraction suggests that muscle pattern generation may be constrained by muscle synergies. [ABSTRACT FROM AUTHOR]

Introduction: Virtual reality (VR) is an advanced technology that creates simulated environments and conditions. By offering the possibility of combining motor, cognitive, and well-being in conjunction with the potential to manipulate multi-sensorial features in a safe environment, VR has emerged as a promising powerful rehabilitation tool. Among advanced VR systems, various authors have highlighted promising effects in the rehabilitation of the computer-assisted rehabilitation environment (CAREN - Motekforce Link; Amsterdam, The Netherlands). In our scoping review, we aimed to map the existing evidence on the use of CAREN in the rehabilitation of neurological patients., Evidence Acquisition: This scoping review was conducted following the PRISMA guidelines. A search was carried out for all peer-reviewed articles published until June 30, 2023, using the following databases: PubMed, Embase, Cochrane Database, PeDro and Web of Science. The following terms have been used: ("Cognitive Rehabilitation" OR "Motor Rehabilitation" OR "CAREN" or "Computer-Assisted Rehabilitation Environment") AND ("Virtual Reality" OR "Rehab")., Evidence Synthesis: From the assessed studies, only seven met the inclusion criteria: 1) one study concerned cognitive rehabilitation in patients suffering from Parkinson's Disease (PD); 2) one was on the usability of CAREN in PD patients; 3) two studies related to the influence of emotional components to CAREN rehabilitation; 4) three studies were related to motor rehabilitation using CAREN, and involved individuals with PD, Multiple Sclerosis, TBI, respectively. Generally, the few assessed studies demonstrate that CAREN is a safe and potentially effective tool to treat different symptoms (including gait and vestibular disturbances, executive function, depressive mood, and anxiety) in patients with different neurological disorders., Conclusions: The reviewed literature indicated the potential use of CAREN in improving motor and cognitive skills with conflicting results on emotional aspects. However, since the data comes from few and small sample size studies, further research is needed to confirm the effectiveness of the tool in neurorehabilitation.

Objective. Magnetic resonance imaging-guided focused ultrasound surgery (MRgFUS) is a non-invasive thermal ablation method that involves high-intensity focused ultrasound surgery (FUS) and Magnetic Resonance Imaging for anatomical imaging and real-time thermal mapping. This technique is widely employed for the treatment of patients affected by essential tremor (ET) and Parkinson's disease (PD). In the current study, functional near-infrared spectroscopy (fNIRS) was used to highlight hemodynamics changes in cerebral cortex activity, during a simple hand motor task, i.e. unimanual left and right finger-tapping, in ET and PD patients. Approach. All patients were evaluated before, one week and one month after MRgFUS treatment. Main results. fNIRS revealed cerebral hemodynamic changes one week and one month after MRgFUS treatment, especially in the ET group, that showed a significant clinical improvement in tremor clinical scores. Significance. To our knowledge, our study is the first that showed the use of fNIRS system to measure the cortical activity changes following unilateral ventral intermediate nucleus thalamotomy after MRgFUS treatment. Our findings showed that therapeutic MRgFUS promoted the remodeling of neuronal networks and changes in cortical activity in association with symptomatic improvements., (Creative Commons Attribution license.)

Objective. Muscle activation patterns in the muscle-to-force null space, i.e. patterns that do not generate task-relevant forces, may provide an opportunity for motor augmentation by allowing to control additional end-effectors simultaneously to natural limbs. Here we tested the feasibility of muscular null space control for augmentation by assessing simultaneous control of natural and extra degrees of freedom. Approach. We instructed eight participants to control translation and rotation of a virtual 3D end-effector by simultaneous generation of isometric force at the hand and null space activity extracted in real-time from the electromyographic signals recorded from 15 shoulder and arm muscles. First, we identified the null space components that each participant could control more naturally by voluntary co-contraction. Then, participants performed several blocks of a reaching and holding task. They displaced an ellipsoidal cursor to reach one of nine targets by generating force, and simultaneously rotated the cursor to match the target orientation by activating null space components. We developed an information-theoretic metric, an index of difficulty defined as the sum of a spatial and a temporal term, to assess individual null space control ability for both reaching and holding. Main results. On average, participants could reach the targets in most trials already in the first block (72%) and they improved with practice (maximum 93%) but holding performance remained lower (maximum 43%). As there was a high inter-individual variability in performance, we performed a simulation with different spatial and temporal task conditions to estimate those for which each individual participants would have performed best. Significance. Muscular null space control is feasible and may be used to control additional virtual or robotics end-effectors. However, decoding of motor commands must be optimized according to individual null space control ability., (© 2022 IOP Publishing Ltd.)

To generate a force at the hand in a given spatial direction and with a given magnitude the central nervous system (CNS) has to coordinate the recruitment of many muscles. Because of the redundancy in the musculoskeletal system, the CNS can choose one of infinitely many possible muscle activation patterns which generate the same force. What strategies and constraints underlie such selection is an open issue. The CNS might optimize a performance criterion, such as accuracy or effort. Moreover, the CNS might simplify the solution by constraining it to be a combination of a few muscle synergies, coordinated recruitment of groups of muscles. We tested whether the CNS generates forces by minimum effort recruitment of either individual muscles or muscle synergies. We compared the activation of arm muscles observed during the generation of isometric forces at the hand across multiple three-dimensional force targets with the activation predicted by either minimizing the sum of squared muscle activations or the sum of squared synergy activations. Muscle synergies were identified from the recorded muscle pattern using non-negative matrix factorization. To perform both optimizations we assumed a linear relationship between rectified and filtered electromyographic (EMG) signal which we estimated using multiple linear regressions. We found that the minimum effort recruitment of synergies predicted the observed muscle patterns better than the minimum effort recruitment of individual muscles. However, both predictions had errors much larger than the reconstruction error obtained by the synergies, suggesting that the CNS generates three-dimensional forces by sub-optimal recruitment of muscle synergies.