Search Results (46)

Subway train operators face the risk of cumulative cognitive stress due to factors such as visual fatigue from prolonged high-speed tunnel driving, irregular shift patterns, and the monotony of automated operations. This can lead to cognitive decline and human error accidents. Current monitoring of cognitive stress risk predominantly relies on single-modal methods, which are susceptible to environmental interference and offer limited accuracy. This study proposes an intelligent multimodal framework for cognitive stress monitoring by leveraging the symmetry principles in physiological and behavioral manifestations. The symmetry of photoplethysmography (PPG) waveforms and the bilateral symmetry of head movements serve as critical indicators reflecting autonomic nervous system homeostasis and cognitive load. By integrating these symmetry-based features, this study constructs a spatiotemporal dynamic feature set through fusing physiological signals such as PPG and galvanic skin response (GSR) with head and facial behavioral features. Furthermore, leveraging deep learning techniques, a hybrid PSO-CNN-GRU-Attention model is developed. Within this model, the Particle Swarm Optimization (PSO) algorithm dynamically adjusts hyperparameters, and an attention mechanism is introduced to weight multimodal features, enabling precise assessment of cognitive stress states. Experiments were conducted using a full-scale subway driving simulator, collecting data from 50 operators to validate the model’s feasibility. Results demonstrate that the complementary nature of multimodal physiological signals and behavioral features effectively overcomes the limitations of single-modal data, yielding significantly superior model performance. The PSO-CNN-GRU-Attention model achieved a predictive coefficient of determination (R²) of 0.89029 and a mean squared error (MSE) of 0.00461, outperforming the traditional BiLSTM model by approximately 22%. This research provides a high-accuracy, non-invasive solution for detecting cognitive stress in subway operators, offering a scientific basis for occupational health management and the formulation of safe driving intervention strategies. Full article

Background: High-intensity actions like accelerations and decelerations, often performed unilaterally, are crucial in elite female football but increase the risk of interlimb asymmetries and injury. Flywheel resistance training enhances eccentric strength, yet limited research has assessed how different inertial loads affect mechanical outputs in unilateral exercises. Purpose: This study investigated how two inertial loads (0.107 kg·m² and 0.133 kg·m²) influence power, acceleration, speed, and asymmetry during unilateral hip extensions in elite female footballers. Methods: Eighteen professional players (27 ± 4 years, 59.9 ± 6.5 kg, 168.2 ± 6.3 cm, BMI 21.2 ± 1.8) completed unilateral hip extensions on a conical flywheel under both inertia conditions. A rotary encoder measured peak/average power, acceleration, speed, and eccentric-to-concentric (E:C) ratios. Bilateral asymmetries between dominant (DL) and non-dominant (NDL) limbs were assessed. Paired t-tests and Cohen’s d were used for analysis. Results: Higher inertia reduced peak and mean acceleration and speed (p < 0.001, d > 0.8). Eccentric peak power significantly increased in the NDL (p < 0.001, d = 3.952). E:C ratios remained stable. Conclusions: Greater inertial loads reduce movement velocity but increase eccentric output in the NDL, offering potential strategies to manage neuromuscular asymmetries in elite female football players. Full article

Upper-limb impairments after stroke significantly affect patients’ quality of life and require effective rehabilitation strategies. Rehabilitation devices play a vital role in enhancing motor recovery. This study evaluated the efficacy of the Arm Booster, a bilateral arm-training device, in improving upper-limb impairment in patients with chronic stroke. Eighteen participants were randomly assigned to two groups: a device group (n = 9), using the Arm Booster; and a conventional physiotherapy group (n = 9). Both groups performed six bilateral upper-limb exercises (32 repetitions each) three times per week for eight weeks. Participants were further classified into mild spasticity (n = 5) and moderate-to-severe spasticity (n = 4) subgroups. The primary outcome was motor impairment, assessed using the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE). Secondary outcomes included spasticity, measured by the Modified Ashworth Scale (MAS), and daily functional use of the arm, assessed with the Motor Activity Log (MAL). Both groups showed significant improvements in FMA-UE scores and overall arm movement. The conventional group demonstrated additional gains in hand and wrist function and coordination. Notably, in the moderate-to-severe spasticity subgroup, the device group exhibited improvements in upper-limb movement and a trend toward reduced spasticity. These findings suggest that the Arm Booster may support motor recovery, encourage the use of the affected arm, improve movement control, and provide an efficient means for patients to exercise more frequently on their own. Full article

We introduce a hybrid deep learning model for recognizing hand gestures from electromyography (EMG) signals in subacute stroke patients: the one-dimensional convolutional long short-term memory neural network (CNN-LSTM). The proposed network was trained, tested, and cross-validated on seven hand gesture movements, collected via EMG from 25 patients exhibiting clinical features of paresis. EMG data from these patients were collected twice post-stroke, at least one week apart, and divided into datasets A and B to assess performance over time while balancing subject-specific content and minimizing training bias. Dataset A had a median post-stroke time of 16.0 ± 8.6 days, while dataset B had a median of 19.2 ± 13.7 days. In classification tests based on the number of gesture classes (ranging from two to seven), the hybrid model achieved accuracies ranging from 85.66% to 82.27% in dataset A and from 88.36% to 81.69% in dataset B. To address the limitations of deep learning with small datasets, we developed a novel bilateral data fusion approach that incorporates EMG signals from the non-paretic limb during training. This approach significantly enhanced model performance across both datasets, as evidenced by improvements in sensitivity, specificity, accuracy, and F1-score metrics. The most substantial gains were observed in the three-gesture subset, where classification accuracy increased from 73.01% to 78.42% in dataset A, and from 77.95% to 85.69% in dataset B. In conclusion, although these results may be slightly lower than those of traditional supervised learning algorithms, the combination of bilateral data fusion and the absence of feature engineering offers a novel perspective for neurorehabilitation, where every data segment is critically significant. Full article

Background: Bilateral movement training (BMT) and interlimb coupling have emerged as promising neurophysiologically-based rehabilitation approaches for stroke survivors. However, the underlying mechanisms and optimal implementation strategies remain incompletely understood. This systematic review explored the neurophysiological principles underlying BMT and interlimb coupling interventions that led to positive clinical post-stroke rehabilitation outcomes, focusing on identifying the most effective bilateral and interlimb movement strategies. Methods: A 10-year literature search (2014–2024) following PRISMA guidelines was conducted across PubMed, Cochrane, and Google Scholar databases using keywords including stroke rehabilitation, bilateral movement training, cross-education, interlimb coupling, and interlimb transfer. Studies were included if they involved human subjects, clinical trials, stroke survivors, and described bilateral training protocols. Data extraction focused on neurophysiological mechanisms, intervention characteristics, and clinical outcomes. Quality assessment was performed using validated methodological appraisal tools, including the Newcastle-Ottawa Scale and Cochrane RoB 2.0. Results: Of 199 initially identified studies, 28 met inclusion criteria for detailed analysis. BMT demonstrated effectiveness in enhancing motor recovery by engaging neurophysiological mechanisms, including central pattern generators, interhemispheric coupling, and cortical disinhibition. High-intensity BMT provided significant gains for individuals with moderate to severe impairments, while low-intensity training benefited early recovery stages. Interventions incorporating task-specific exercises, robotic assistance, sensory enhancement, and virtual reality showed particular promise for addressing motor recovery complexities. However, significant research gaps were identified, including limited understanding of individualized responses to BMT, insufficient research on combined upper and lower limb training, and minimal integration of advanced technologies. Conclusions: BMT and interlimb coupling play critical roles in post-stroke rehabilitation by facilitating neural plasticity and interlimb coordination. Integrating robotic assistance, sensory enhancement, and virtual reality with BMT offers a robust framework for maximizing rehabilitation outcomes. Future research should prioritize longitudinal studies, personalized rehabilitation approaches, technology integration, and stratified interventions tailored to individual needs to optimize neuroplasticity and enhance quality of life for stroke survivors. Full article

Functional transcranial Doppler (fTCD) ultrasound can detect cerebral blood flow lateralization to the left/right hemisphere during different tasks. This study aims to test the effectiveness of neurofeedback in improving the individual capacity to lateralize blood flow with mental activity. Bilateral monitoring of blood velocity (CBV) in the middle cerebral arteries was performed in 14 subjects engaged in 15 min of training, followed by a 15 min test in each of four sessions. A ball, displayed on a screen, moved right or left, according to the current right/left difference in normalized CBVs, thus providing a visual neurofeedback of lateralization. The subjects were invited to control the left/right movement of the depicted ball by appropriately orienting their mental activity, freely exploring different strategies. These attempts were completely free and unsupervised during training, while during the test, the subjects were required to follow randomized left/right cues lasting 35 s. Performance was assessed using receiver operating characteristic (ROC) analysis. With training, responses to left and right cues diverged more rapidly and consistently. Accuracy improved significantly from 0.51 to 0.65, and the area under the ROC increased from 0.55 to 0.69. These results demonstrate the effectiveness of neurofeedback in improving lateralization capacity, with implications for the development of fTCD-based brain–computer interfaces. Full article

Background/Objectives: Shoulder injuries are common in overhead sports like tennis due to repetitive unilateral movements that can lead to muscle imbalances. This study aimed to compare muscle recruitment and asymmetry during bilateral shoulder injury prevention exercises (performed with both arms simultaneously) in tennis players versus non-tennis athletes. Methods: Thirty-nine athletes (sixteen tennis players, twenty-three non-tennis athletes) performed two bilateral scapular retraction exercises at 45° and 90° shoulder abduction. Surface electromyography (sEMG) recorded the activation of the middle and lower trapezius. Root Mean Square (RMS), peak RMS and muscle symmetry indices were analyzed. Results: Tennis players showed significantly lower trapezius activation, especially during prone retraction at 90°. Muscle symmetry was slightly higher in tennis players at 90°, but asymmetry increased at 45°, suggesting angle-specific adaptations. Conclusions: Repetitive asymmetric loading in tennis may reduce the activation of scapular stabilizers and contribute to muscular imbalances. Including targeted bilateral exercises in training may help improve scapular muscle function and reduce injury risk in overhead athletes. Full article

Purpose: Patients with advanced glaucoma have visual field defects that impair mobility and quality of life (QoL). We aim to determine the effects of exploratory saccade training (EST) in such patients with bilateral overlapping scotomas that affect at least one visual field quadrant. Patients and Methods: This study was approved by the Ethics Committee of the Medical Faculty of the University of Tuebingen, Germany, and was registered in the German Clinical Trials Register (DRKS DRKS00031082, date of approval: 2 February 2023). We randomly assigned 27 patients to two groups, one of which trained with a computer-based EST (group 1). A control group (group 2) first used reading training (rapid serial visual presentation, RSVP, a single-word presentation to minimize eye movements) as placebo training (PRT) in regard to EST, which trains eye movements and, in a later phase, also used EST. Each training method required 6 weeks of home training. Main outcome variables were reaction time (RT) during the EST training sessions, RT during a natural search task (table test), reading speed (RS) during training on the screen, and during reading printed paragraphs aloud. QoL was assessed by a questionnaire. Results: Reaction times during EST and the table test improved significantly, which indicated transfer of the training effect to daily life. RS and QoL were reduced at baseline. Reading training improved RS significantly and reached normal median values. QoL improved significantly in the sub-categories regarding mobility problems in group 1. Patients with inferior field defects were more impaired and improved more than those without inferior field defects. Conclusions: As a supplement to the necessary treatment for glaucoma, EST is an effective home training method for rehabilitation by improving reaction time in daily living tasks for patients with advanced glaucoma. Reading training improved RS while reading from a screen as well as reading printed text. Full article

Background/Objectives: Repeated spiking and serving movements in volleyball can lead to alterations in shoulder range of motion among athletes, potentially increasing the risk of shoulder instability and injury. Hence, assessing and understanding the shoulder range of motion of volleyball players is a critical concern. Therefore, this study aimed to understand and evaluate the bilateral shoulder joint range of motion (ROM) in high-school male volleyball athletes and to discover the adaptation characteristics. Methods: Forty high-school male volleyball athletes participated in this study. Shoulder ROM measurements were taken via video with an iPhone 12 Pro Max, and we analyzed the ROM data using Kinovea software (Version 0.9.5) for both the dominant and non-dominant side. The shoulder ROM measurements included shoulder hyper-extension (SE), flexion (SF), internal rotation (IR), external rotation (ER), horizontal adduction (Sadd), and horizontal abduction (Sabd). After taking shoulder ROM measurements, the total rotational range of motion (TROM) was calculated based on the participants’ shoulder internal rotation and external rotation data, and we calculated the incidence of glenohumeral internal rotation deficiency (GIRD) among participants. Paired samples t-tests were used to analyze shoulder ROM differences between the dominant and non-dominant side. Results: The dominant side of the shoulder showed significantly lower internal rotation (dominant side: 42.17 ± 11.23°; non-dominant side: 52.14 ± 10.46°; p = 0.000) and total rotational ROM (dominant side: 137.11 ± 13.09°; non-dominant side: 141.96 ± 13.22°; p = 0.021) compared to the non-dominant side. Conversely, the dominant side of the shoulder exhibited significantly greater external rotation (dominant side: 94.96 ± 10.02°; non-dominant side: 89.83 ± 7.84°; p = 0.001) and shoulder horizontal adduction (dominant side: 44.87 ± 8.10°; non-dominant side: 39.60 ± 7.24°; p = 0.000) than the non-dominant side. No significant differences were found in other measured parameters. The incidence of glenohumeral internal rotation deficiency (GIRD) among all subjects was 37.5%. Conclusions: High-school male volleyball athletes in this study exhibited tightness in the posterior shoulder of their dominant side, indicating specific adaptations in shoulder ROM and a considerable prevalence of GIRD, observed in approximately one-quarter of the athletes. In conclusion, these data suggest that stretching and eccentric muscle training focusing on the posterior shoulder have potential value in mitigating these adaptations and reducing the risk of shoulder injuries. Full article

Motor impairment is a critical health issue that restricts disabled people from living their lives normally and with comfort. Detecting motor imagery (MI) in electroencephalography (EEG) signals can make their lives easier. There has been a lot of work on detecting two or four different MI movements, which include bilateral, contralateral, and unilateral upper limb movements. However, there is little research on the challenging problem of detecting more than four motor imagery tasks and unilateral lower limb movements. As a solution to this problem, a spectral-spatio-temporal multiscale network (SSTMNet) has been introduced to detect six imagery tasks. It first performs a spectral analysis of an EEG trial and attends to the salient brain waves (rhythms) using an attention mechanism. Then, the temporal dependency across the entire EEG trial is worked out using a temporal dependency block, resulting in spectral-spatio-temporal features, which are passed to a multiscale block to learn multiscale spectral-–spatio-temporal features. Finally, these features are deeply analyzed by a sequential block to extract high-level features, which are used to detect an MI task. In addition, to deal with the small dataset problem for each MI task, the researchers introduce a data augmentation technique based on Fourier transform, which generates new EEG trials from EEG signals belonging to the same class in the frequency domain, with the idea that the coefficients of the same frequencies must be fused, ensuring label-preserving trials. SSTMNet is thoroughly evaluated on a public-domain benchmark dataset; it achieves an accuracy of 77.52% and an F1-score of 56.19%. t-SNE plots, confusion matrices, and ROC curves are presented, which show the effectiveness of SSTMNet. Furthermore, when it is trained on augmented data generated by the proposed data augmentation method, it results in a better performance, which validates the effectiveness of the proposed technique. The results indicate that its performance is comparable with the state-of-the-art methods. An analysis of the features learned by the model reveals that the block architectural design aids the model in distinguishing between multi-imagery tasks. Full article

The present study aimed to evaluate the effects of 12-week resistance training (RT) on muscle strength, dynamic balance, glycemic control and the lipid profile. Methods: The Laboratory of Movement Studies in the University of São Paulo, Brazil, developed this longitudinal study between 2021 and 2023. It assessed 62 males with type 2 diabetes mellitus pre and post an RT protocol. The participants, who were 69.8 (±3.9) years old, took part in a 12-week twice-weekly RT program. Three sets of eight to twelve repetitions each were executed for eight exercises targeting the large muscle groups. The intensity was set between 7 and 8 out of 10 for perceived effort, according to the Omni Resistance Exercise Scale. All participants were evaluated pre and post in knee extensor and flexor strength by isokinetic dynamometry, handgrip strength by manual dynamometry and dynamic postural balance by a force platform, as well as blood tests to determine the lipid and glycemic profiles. For comparison, paired t or Wilcoxon tests were used at an alpha of 5%. Results: There was an improvement in muscular strength by handgrip restricted to the non-dominant side (p = 0.033) and for the bilateral knee flexors (p < 0.001) and extensors (p < 0.001), as determined by isokinetic dynamometry. There was no improvement in dynamic postural balance, glycemic control or lipid control. Conclusions: The 12-week RT promoted improved muscle strength in knee extension and flexion and non-dominant grip pressure but did not affect dynamic balance, glycemic control or the lipid profile. Full article

Background/Objectives: The main objective of this manuscript is to evaluate the effects of training, music, and movement intervention on motor functions, social engagement, and behaviors in autistic children. Methods: Twenty-one children with a diagnosis of mild autism spectrum disorder (ASD), with an age range of 5-to-13 years, were divided into two groups: the experimental group (n = 10) and the control group (n = 11). All participants were examined before (T0) and after the intervention (T1) to evaluate their motor functions (Bruininks–Oseretsky Motor Performance Test (BOT-2)), maladaptive behavior (RCS (Response to Challenge Scale)), and enjoyment and engagement (PACES (Physical Activity Enjoyment Scale)). Results: Statistical analysis showed that music and movement intervention significantly improved motor functions such as balance and bilateral coordination (p < 0.0001), social engagement (p = 0.002), and adaptive behaviors (p = 0.005) in children with ASD. Our research supports the feasibility of music and movement intervention and documents the interest in participating in children with ASD. Conclusions: This study demonstrates the benefits of movement and music interventions and can be considered a useful way to manage autism spectrum disorders in the future. Full article

Soft exoskeletons (exosuits) are expected to provide a comfortable wearing experience and compliant assistance compared with traditional rigid exoskeleton robots. In this paper, an exosuit with twisted string actuators (TSAs) is developed to provide high-strength and variable-stiffness actuation for hemiplegic patients. By formulating the analytic model of the TSA and decoding the human impedance characteristic, the human-exosuit coupled dynamic model is constructed. An adaptive impedance controller is designed to transfer the skills of the patient’s healthy limb (HL) to the bilateral impaired limb (IL) with a mirror training strategy, including the movement trajectory and stiffness profiles. A reinforcement learning (RL) algorithm is proposed to optimize the robotic assistance by adapting the impedance model parameters to the subject’s performance. Experiments are conducted to demonstrate the effectiveness and superiority of the proposed method. Full article

This study aimed to evaluate the efficacy of rTMS in treating sleep disorders in PD. It included 24 patients with PD who had sleep disorders. Group allocations (active or sham with a ratio of 2:1) were placed in serially numbered closed envelopes. Each patient was evaluated with the following: MDS-UPDRS, Parkinson’s Disease Sleep Scale (PDSS), Beck Depression Inventory (BDI), and polysomnography (PSG) before and 10 days after the treatment sessions. Each session consisted of 10 trains, 20 Hz, 10 sec for each, over the parietal cortex (bilaterally). Scores of UPDRS, BDI, and PDSS improved significantly in the active group but not in the sham group. The PSG data showed that sleep onset and rapid eye movement (REM) latencies (min), REM duration, and time spent awake (both as %TST) were improved after rTMS in the active group compared with the sham group. The number of awakenings, the wake-after-sleep onset index, the arousal index, and periodic leg movements (PLMs) were all significantly reduced in the active group but not in the sham group. Ten sessions of 20 Hz rTMS over parietal cortexes improved sleep quality and PLMs in patients with PD. The improvement in PSG and PDSS were correlated with improvements in UPDRS and BDI scores. Full article

The implementation of a progressive rehabilitation training model to promote patients’ motivation efforts can greatly restore damaged central nervous system function in patients. Patients’ active engagement can be effectively stimulated by assist-as-needed (AAN) robot rehabilitation training. However, its application in robotic therapy has been hindered by a simple determination method of robot-assisted torque which focuses on the evaluation of only the affected limb’s movement ability. Moreover, the expected effect of assistance depends on the designer and deviates from the patient’s expectations, and its applicability to different patients is deficient. In this study, we propose a control method with personalized treatment features based on the idea of estimating and mapping the stiffness of the patient’s healthy limb. This control method comprises an interactive control module in the task-oriented space based on the quantitative evaluation of motion needs and an inner-loop position control module for the pneumatic swing cylinder in the joint space. An upper-limb endpoint stiffness estimation model was constructed, and a parameter identification algorithm was designed. The upper limb endpoint stiffness which characterizes the patient’s ability to complete training movements was obtained by collecting surface electromyographic (sEMG) signals and human–robot interaction forces during patient movement. Then, the motor needs of the affected limb when completing the same movement were quantified based on the performance of the healthy limb. A stiffness-mapping algorithm was designed to dynamically adjust the rehabilitation training trajectory and auxiliary force of the robot based on the actual movement ability of the affected limb, achieving AAN control. Experimental studies were conducted on a self-developed pneumatic upper limb rehabilitation robot, and the results showed that the proposed AAN control method could effectively estimate the patient’s movement needs and achieve progressive rehabilitation training. This rehabilitation training robot that simulates the movement characteristics of the patient’s healthy limb drives the affected limb, making the intensity of the rehabilitation training task more in line with the patient’s pre-morbid limb-use habits and also beneficial for the consistency of bilateral limb movements. Full article