Search Results (7,504)

Background and Objectives: Toe walking (TW) is frequently observed in children with Autism Spectrum Disorder (ASD), yet its clinical significance and association with comorbid conditions remain poorly understood. This study aimed to examine the prevalence of TW in a large Italian cohort of children with ASD and to explore its association with ASD severity, sleep disturbances, feeding behaviors, and gastrointestinal symptoms. Materials and Methods: A total of 289 children with ASD and 289 typically developing controls (TDC), matched for age and sex, were evaluated in a multicentric observational study. TW was assessed during neurodevelopmental evaluations. Sleep quality was assessed using the Sleep Disturbance Scale for Children (SDSC), feeding behaviors via the Brief Autism Mealtime Behavior Inventory (BAMBI), and gastrointestinal symptoms through clinical reporting. Statistical analyses included Chi-square tests, Mann–Whitney U tests, Spearman correlations, and logistic regressions. Results: TW was significantly more prevalent in the ASD group (27.3%) than in TDC (5.5%, p < 0.0001). Within the ASD group, TW occurred in 50.5% of children with Level 3 severity but was absent in Levels 1 and 2 (p < 0.0001). Males exhibited TW more frequently than females. Children with TW had higher SDSC scores (ρ = 0.33, p < 0.0001), though no subscale independently predicted TW. Constipation was reported in 100% of children with Level 3 ASD and was strongly correlated with SDSC total scores (ρ = 0.58, p < 0.0001). The Disorders of Arousal (DA) subscale emerged as an independent predictor of constipation (β = 0.184, p = 0.019). Conclusions: TW in ASD appears to be a marker of greater neurodevelopmental severity and is associated with sleep disturbances and gastrointestinal dysfunction. These findings support the hypothesis that TW may reflect broader dysfunctions involving the gut–brain axis, sensory processing, and motor control. The routine clinical assessment of TW should include the evaluation of sleep and somatic symptoms to better understand the multisystemic nature of ASD phenotypes. Full article

Purpose: Integrated neuromuscular training (INT) is a multidimensional training method that integrates strength, balance, core stability, flexibility, and motor skill development. The aim of this study was to systematically evaluate the effects of INT on various physical performance indicators in athletes to provide evidence supporting the application of INT in training practices. Method: A systematic search was conducted in accordance with PRISMA guidelines across nine databases—including PubMed, Web of Science, EMBASE, Scopus, Cochrane Library, Ovid MEDLINE, WILEY, and Springer Nature Link—from inception to 26 March 2025 to identify randomized controlled trials (RCTs) examining the effects of INT on athletic performance. Result: A total of 19 randomized controlled trials were included, comprising 783 participants aged 11–25 years. The meta-analysis results indicated that INT significantly improved jump performance (SMD = 0.26, 95% CI [0.15, 0.37], p < 0.001, I² = 75%), sprint performance (SMD = −0.76, 95% CI [−0.93, −0.58], p < 0.001, I² = 76%), balance performance (SMD = 0.23, 95% CI [0.14, 0.31], p < 0.001, I² = 78%), and agility performance (SMD = −0.72, 95% CI [−1.23, −0.21], p < 0.05, I² = 74%). Sensitivity analyses revealed no substantial changes in jump, sprint, agility, or balance performance outcomes. Conclusions: INT was found to significantly improve sprint, jump, balance, and agility performance in athletes. Analysis of the included training protocols suggested that improvements in each performance indicator required emphasis on specific training components. Moreover, greater improvements in sprint and balance performance were observed in female athletes compared to their male counterparts. Subgroup analysis revealed significant differences in training effects across populations, with female athletes showing superior improvements in sprint and balance performance following INT interventions. Additionally, interventions lasting fewer than eight weeks, with training sessions shorter than 30 min and frequencies of more than three times per week, were associated with more pronounced effects. Full article

SYNGAP1-related disorder is a rare neurodevelopmental disorder characterized by intellectual and motor disabilities, including disordered gait control. Currently, there have been few studies that have assessed the gait of individuals with SYNGAP1-related disorder using technology-based collection techniques. The purpose of this investigation was to characterize the kinematic gait pattern of these individuals using camera-based motion capture technology during treadmill walking. Both linear and non-linear analysis techniques were used to analyze bilateral lower-limb joint motion and compare the results to age-matched neurotypical individuals. Results indicate that joint range of motion and velocity were decreased in the patient population relative to the neurotypical participants with the non-linear measures of angle–angle and phase portrait areas reflecting similar outcomes. The combination of linear and non-linear measures provide complementary information that, when used in combination, can provide deeper insights into the coordination and control of gait than if either of the measurement techniques are used in isolation. Such information can be useful to clinicians and therapists to develop targeted interventions designed to improve the gait of individuals with SYNGAP1-related disorder. Full article

This work presents a novel type of soft reconfigurable mobile robot with multimodal locomotion, which is created using a controllable magneto-elastica-reinforced composite elastomer. The rope motor-driven method is employed to modulate magnetics–mechanics coupling effects and enable the magneto-elastica-reinforced elastomer actuator to produce controllable deformations. Furthermore, the 3D-printed magneto-elastica-reinforced elastomer actuators are assembled into several typical robotic patterns: linear configuration, parallel configuration, and triangular configuration. As a proof of concept, a few of the basic locomotive modes are demonstrated including squirming-type crawling at a speed of 1.11 $\mathrm{m}\mathrm{m}/\mathrm{s}$, crawling with turning functions at a speed of 1.11 $\mathrm{m}\mathrm{m}/\mathrm{s}$, and omnidirectional crawling at a speed of 1.25 $\mathrm{m}\mathrm{m}/\mathrm{s}$. Notably, the embedded magnetic balls produce magnetic adhesion on the ferromagnetic surfaces, which enables the soft mobile robot to climb upside-down on ferromagnetic curved surfaces. In the experiment, the inverted ceiling-based inverted crawling speed is 2.17 $\mathrm{m}\mathrm{m}/\mathrm{s}$, and the inverted freeform surface-based inverted crawling speed is 3.40 $\mathrm{m}\mathrm{m}/\mathrm{s}$. As indicated by the experimental results, the proposed robot has the advantages of a simple structure, low cost, reconfigurable multimodal motion ability, and so on, and has potential application in the inspection of high-value assets and operations in confined environments. Full article

Muscle–joint flexibility is defined as the ability of a muscle to stretch in a controlled manner, allowing a wide range of movement at the joints. While numerous methodologies exist for improving flexibility, few studies have investigated the role of athletes’ perceptual processes and awareness related to their own body and movement control during such training. In this pilot study, we explored how two different training protocols—static and dynamic stretching (control group, CON) and multi-joint resistance training (experimental group, EXP)—influence both flexibility and psychophysical awareness, understood as a multidimensional construct involving perceived flexibility improvements, self-assessed control over exercise execution, and cognitive-emotional responses such as engagement, motivation, and satisfaction during physical effort. The study involved 24 male amateur track-and-field athletes (mean age 23 ± 2.5 years), randomized into two equal groups. Over 12 weeks, both groups trained three times per week. Flexibility was assessed using the Sit and Reach Test at three time points (pre-, mid-, and post-intervention). A 2 × 3 mixed ANOVA revealed a significant group × time interaction (F = 20.17, p < 0.001), with the EXP group showing greater improvements than the CON group. In the EXP group, Sit and Reach scores increased from pre = 28.55 cm (SD = 4.91) to mid = 29.39 cm (SD = 4.67) and post = 29.48 cm (SD = 4.91), with a significant difference between pre and post (p = 0.01; d = 0.35). The CON group showed minimal changes, with scores of pre = 28.66 cm (SD = 4.92), mid = 28.76 cm (SD = 5.03), and post = 28.84 cm (SD = 5.10), and no significant difference between pre and post (p = 0.20; d = 0.04). Psychophysical awareness was assessed using a custom questionnaire structured on a 5-point Likert scale, with items addressing perception of flexibility, motor control, and exercise-related bodily sensations. The questionnaire showed excellent internal consistency (Cronbach’s α = 0.92). Within the EXP group, psychophysical awareness increased significantly (from 3.50 to 4.17; p = 0.01; d = 0.38), while no significant change occurred in the CON group (p = 0.16). Post-hoc power analysis confirmed small to moderate effect sizes within the EXP group, although between-group differences lacked sufficient statistical power. These results suggest that resistance training may improve flexibility and concurrently enhance athletes’ psychophysical self-awareness more effectively than traditional stretching. Such findings offer practical implications for coaches seeking to optimize flexibility training by integrating alternative methods that promote both physical and perceptual adaptations. Full article

Background: Epidemiological studies have reported an inverse association between smoking and Parkinson’s disease (PD) risk, prompting interest in nicotine as a potential therapeutic agent. The present meta-analysis evaluated the efficacy of nicotine therapy in improving motor symptoms and activities of daily living in patients with PD. Methods: PubMed, Embase, and Cochrane Library were systematically searched to identify randomized controlled trials (RCTs) assessing nicotine therapy in PD. Clinical RCTs administering interventions extending beyond 1 week and reporting motor or nonmotor outcomes were included. Random-effects models were used to analyze short-term (<6 months) and long-term (≥6 months) outcomes by using standardized mean differences (SMDs). Results: This meta-analysis included five RCTs (346 participants). Nicotine therapy led to no significant improvement in motor outcomes in the short term (pooled SMD: −0.452, 95% confidence interval: −1.612 to 0.708) or long term (pooled SMD: 0.174, 95% confidence interval: −0.438 to 0.787). Considerable interstudy heterogeneity was noted. Furthermore, short-term nicotine therapy resulted in no significant improvement in daily functioning, cognition, or quality of life. Conclusions: This meta-analysis revealed a lack of compelling evidence suggesting that nicotine-based therapies improve motor or nonmotor outcomes in PD. The findings highlight a disconnect between epidemiological associations and clinical efficacy. Given the prodromal nature of PD pathology and the challenges of early diagnosis, future preventive strategies should be implemented before symptom onset in high-risk individuals identified using advanced biomarker panels. Full article

This paper studies the adaptive practical tracking control (PTC) problem for a class of uncertain nonlinear systems (UNSs) with nontriangular structured uncertain terms and unknown parameters, where the boundary of nontriangular structured uncertain terms depends on all state variables. Based on the improved adaptive backstepping technique, the state feedback tracking controller and update laws are first constructed. Then, by seeking the linear relationship between the state vector and the error vector, and by utilizing the comparison principle, it is verified that the developed adaptive PTC scheme can ensure that all signals of the closed-loop system are bounded and the tracking error converges to a bounded region. Finally, two examples, including a numerical example and the dual-motor drive servo system, are provided to show the effectiveness of this control method. Full article

Objective: The objective of the study was to investigate the relationship between the level of physical activity and body composition, and the levels of motor skills and strength in overweight and obese men. Methods: The research involved 64 men. Body composition, physical activity, motor control, Motor Control Test (MCT), and strength variables were evaluated. Body composition was assessed by DXA, and the participants were classified into two groups according to the percentage of total fat mass: greater and less than 27.65%. Physical activity was assessed using accelerometry, and motor control was measured with posturography, which provided a composite score of motor performance and postural control effectiveness. Strength was assessed using hand, leg, and back dynamometers. Results: The participants with a higher percentage of body fat had a lower DSI (Dynamic Strength Index) (p < 0.001) and significantly reduced PAL (physical activity level) and energy expenditure (p < 0.001). No significant differences were found in the muscle strength of the upper limbs (p = 0.06) and lower limbs (p = 0.419). With regard to MCT, there was a significant difference between groups in the backward direction (p = 0.041), with the group with the highest percentage of body fat showing lower values. Conclusions: Individuals with a higher percentage of body fat tend to have lower levels of strength, physical activity, and energy expenditure, which can lead to impaired balance. The findings highlight the need for targeted interventions to improve body composition and levels of strength and physical activity, with a positive impact on general health and quality of life. Emphasis should be placed on improving physical activity levels in male individuals with a higher percentage of fat mass to improve their body composition and dynamic strength levels, which are beneficial to life, particularly to help improve postural control. Full article

In the context of the mining industry, the belt conveyor is a critical piece of equipment. The motor constitutes the primary component of the belt conveyor apparatus, and its stable and accurate operation can significantly influence the performance of the belt conveyor apparatus. This paper introduces an integrated control approach combining vector control methodology with active disturbance rejection control (ADRC) for velocity regulation and model predictive control (MPC) for current tracking. The ADRC framework actively compensates for load disturbances and parameter variations during speed control, while MPC achieves precise current regulation with minimal tracking error. Validation involved comprehensive MATLAB/Simulink R2024a simulations modeling PMSM behavior under mining-specific operating conditions. The results demonstrate substantial improvements in dynamic response characteristics and disturbance rejection capabilities compared to conventional control strategies. The proposed methodology effectively addresses critical challenges in mining conveyor applications, enhancing operational reliability and system longevity. Full article

Parkinson’s disease (PD) is a progressive neurological disorder with motor and non-motor symptoms that are inadequately addressed by current pharmacological and surgical therapies. Brain–computer interfaces (BCIs), particularly those based on electroencephalography (eBCIs), provide a promising, non-invasive approach to personalized neurorehabilitation. This narrative review explores the clinical potential of BCIs in PD, discussing signal acquisition, processing, and control paradigms. eBCIs are well-suited for PD due to their portability, safety, and real-time feedback capabilities. Emerging neurophysiological biomarkers—such as beta-band synchrony, phase–amplitude coupling, and altered alpha-band activity—may support adaptive therapies, including adaptive deep brain stimulation (aDBS), as well as motor and cognitive interventions. BCIs may also aid in diagnosis and personalized treatment by detecting these cortical and subcortical patterns associated with motor and cognitive dysfunction in PD. A structured search identified 11 studies involving 64 patients with PD who used BCIs for aDBS, neurofeedback, and cognitive rehabilitation, showing improvements in motor function, cognition, and engagement. Clinical translation requires attention to electrode design and user-centered interfaces. Ethical issues, including data privacy and equitable access, remain critical challenges. As wearable technologies and artificial intelligence evolve, BCIs could shift PD care from intermittent interventions to continuous, brain-responsive therapy, potentially improving patients’ quality of life and autonomy. This review highlights BCIs as a transformative tool in PD management, although more robust clinical evidence is needed. Full article

This paper presents the application of a sliding mode observer for speed sensorless control of a six-phase induction machine. The use of nonlinear sliding mode techniques yields acceptable performance for both low- and high-speed motor operations over a wide speed range. The effectiveness and accuracy of the developed sensorless scheme are verified by experimental results, which demonstrate the system’s performance under various operating conditions. These results demonstrate the advantages of the proposal as a valid alternative to the conventional method, which uses a mechanical speed sensor for multiphase machines. Additionally, the sensorless approach can also serve as a redundant backup in the event of mechanical sensor failure, thereby increasing the reliability of the overall drive system. Full article

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that primarily affects motor neurons, leading to loss of muscle control, and, ultimately, respiratory failure and death. Despite some advances in recent years, the underlying genetic and molecular mechanisms of ALS remain largely elusive. In this respect, a better understanding of these mechanisms is needed to identify new and biologically relevant therapeutic targets that could be developed into treatments that are truly disease-modifying, in that they address the underlying causes rather than the symptoms of ALS. In this study, we used two approaches to model multi-omics data in order to map and elucidate the genetic and molecular mechanisms involved in ALS, i.e., the molecular landscape building approach and the Patrimony platform. These two methods are complementary because they rely upon different omics data sets, analytic methods, and scoring systems to identify and rank therapeutic target candidates. The orthogonal combination of the two modeling approaches led to significant convergences, as well as some complementarity, both for validating existing therapeutic targets and identifying novel targets. As for validating existing targets, we found that, out of 217 different targets that have been or are being investigated for drug development, 10 have high scores in both the landscape and Patrimony models, suggesting that they are highly relevant for ALS. Moreover, through both models, we identified or corroborated novel putative drug targets for ALS. A notable example of such a target is MATR3, a protein that has strong genetic, molecular, and functional links with ALS pathology. In conclusion, by using two distinct and highly complementary disease modeling approaches, this study enhances our understanding of ALS pathogenesis and provides a framework for prioritizing new therapeutic targets. Moreover, our findings underscore the potential of leveraging multi-omics analyses to improve target discovery and accelerate the development of effective treatments for ALS, and potentially other related complex human diseases. Full article

Background and Objectives: Cerebral palsy (CP) is a non-progressive neurological disorder characterized by motor impairments such as spasticity and poor postural control. Among these, trunk control plays a critical role in maintaining balance and enabling functional mobility. Since spasticity is known to interfere with motor coordination and posture, evaluating its response to trunk-focused interventions may offer additional clinical insights. This systematic review and meta-analysis evaluated the effectiveness of trunk-focused interventions on trunk control, gross motor function, balance, and spasticity. Materials and Methods: A systematic search was conducted in PubMed, Embase, Web of Science, MEDLINE, and CINAHL for randomized controlled trials (RCTs) published in the last 10 years up to 11 April 2023. Studies targeting trunk-specific interventions in children with CP were included. Meta-analyses were performed using RevMan 5.3, calculating standardized mean differences (SMDs) with 95% confidence intervals (CIs). Study quality was assessed using the PEDro scale. Results: Fifteen RCTs involving 454 children were included. Trunk control improved significantly (SMD = 3.67; 95% CI: 3.10–4.25; I² = 0%). Gross motor function showed a small but significant improvement (SMD = 0.49; 95% CI: 0.06–0.92; I² = 44%). Balance exhibited a large, though not statistically significant, effect (SMD = 0.90; 95% CI: −0.00 to 1.79; I² = 81%). Subgroup analysis indicated that interventions performed more than four times per week produced a significant effect on balance (SMD = 0.54; 95% CI: 0.08–1.01). Only one study assessed spasticity and found no group difference. Conclusions: Trunk-based interventions significantly improve trunk control and gross motor function in children with CP. While improvements in balance were inconsistent, higher-frequency interventions yielded more favorable results. Further research is warranted to clarify effects on spasticity and optimize intervention protocols for clinical application. Full article

Digital Twins (DTs) are transforming manufacturing by bridging the physical and digital worlds, enabling real-time insights, predictive analytics, and enhanced decision making. In Industry 4.0, DTs facilitate automation and data integration, while Industry 5.0 emphasizes human-centric, resilient, and sustainable production. However, implementing DTs in robotic metal additive manufacturing (AM) remains challenging because of the complexity of the wire-based laser metal deposition (LMD) process, the need for real-time monitoring, and the demand for advanced defect detection to ensure high-quality prints. This work proposes a structured DT architecture for a robotic wire-based LMD cell, following a standard framework. Three DT implementations were developed. First, a real-time 3D simulation in RoboDK, integrated with a 2D Node-RED dashboard, enabled motion validation and live process monitoring via MQTT (message queuing telemetry transport) telemetry, minimizing toolpath errors and collisions. Second, an Industrial IoT-based system using KUKA iiQoT (Industrial Internet of Things Quality of Things) facilitated predictive maintenance by analyzing motor loads, joint temperatures, and energy consumption, allowing early anomaly detection and reducing unplanned downtime. Third, the Meltio dashboard provided real-time insights into the laser temperature, wire tension, and deposition accuracy, ensuring adaptive control based on live telemetry. Additionally, a prescriptive analytics layer leveraging historical data in FireStore was integrated to optimize the process performance, enabling data-driven decision making. Full article

With the frequent occurrence of global floods, the demand for emergency rescue equipment has grown rapidly. The development and technological innovation of digital hydraulic drive systems (DHDSs) for emergency drainage pumps (EDPs) have become key to improving rescue efficiency. However, EDPs are prone to being affected by random and uncertain loads during operation. To achieve intelligent and efficient rescue operations, a DHDS suitable for EDPs was proposed. Firstly, the configuration and operation mode of the DHDS for EDPs were analyzed. Based on this, a multi-field coupling dynamic simulation platform for the DHDS was constructed. Secondly, the output characteristics of the system under alternating loads were simulated and analyzed. Finally, a test platform for the EDP DHDS was established, and the dynamic characteristics of the system under alternating loads were explored. The results show that as the load torque of the alternating loads increases, the amplitude of the pressure of the motor also increases, the output flow of the hydraulic-controlled proportional reversing valve (HCPRV) changes slightly, and the fluctuation range of the rotational speed of the motor increases. The fluctuation range of the pressure and the rotational speed of the motor are basically not affected by the frequency of alternating loads, but the fluctuation amplitude of the output flow of the HCPRV reduces with the increase in the frequency of alternating loads. This system can respond to changes in load relatively quickly under alternating loads and can return to a stable state in a short time. It has laudable anti-interference ability and output stability. Full article