Entire Motor Research Articles

In-Depth Research on the Behavioral Impact of Violence-Oriented Cartoons among Children

One significant experience in children's early life is watching cartoons. This activity has a significant impact on a variety of variables, including kids' behavioral and cognitive development. This study focuses on school-age children, namely those in the 4–13 age range. This study focuses on the effects of the Violence-Oriented Cartoons channel on children's entire development, including language, motor, social learning, social cognitive, and moral development. 500 samples from various ages of children’s Group A and Group B were gathered for this investigation. This study aims to investigate the behavioral and emotional effects of exposure to violence-oriented cartoons on children. In particular, it aims to evaluate the effects of this type of social behavior, aggressiveness levels, attention span, emotional reactions, and the desensitization of violence in comparison to nonviolent cartoons. Using a sample of 500 children, 200 were exposed to non-violence-oriented cartoons and 300 were exposed to violence-oriented cartoons. The study used two groups. The study highlights that children who watched violent cartoons showed significantly higher levels of aggression, lower social behavior, shorter attention spans, increased desensitization, and stronger negative emotional responses than children who watched nonviolent cartoons. Study finds the importance of careful consideration of children's media content and suggests the potential benefits of limiting exposure to violent imagery in cartoons.

Foot pressure transfers are altered in lumbar radiculopathy but reversible after surgery: a prospective, pedobarography study

BACKGROUND CONTEXTPatients with lower lumbar stenosis and disc herniation report disability in standing and ambulation, despite normal neurological examination. The L5 and S1 nerve roots support the entire motor and sensory function of the foot, and their radiculopathy can affect foot loading during standing and walking. This has not been quantified before. PURPOSETo quantify alterations in static and dynamic foot pressure transfers in patients with lower lumbar nerve root compression, and document any beneficial effects of surgical decompression. STUDY DESIGNProspective, case-control study. PATIENT SAMPLECases—Patients with unilateral radiculopathy (L5/S1) with normal neurology (n=50); Controls - Healthy volunteers (n=50). METHODSThe volunteers and patients underwent pedobarographic analysis during standing (static) and walking (dynamic), and fifteen (12 dynamic and three static) parameters were documented. The patient's preoperative values were compared with that of the healthy volunteers. All the 50 patients underwent surgical decompression, and clinical outcome measures (VAS/ODI at 3 months) were documented. Pedobarographic analysis was repeated in the postoperative period (48 hours) and 3-month follow-up and compared with the preoperative scores. RESULTSIn healthy controls, the mean values of all 15 parameters were comparable between the right and the left side (p>.05). When compared to controls, the patients had significantly lower maximum foot loads (p=.01) and average foot loads (p=.05) on the affected side during walking indicating lesser load transmission, in the preoperative period. Within the affected foot, the load transfer was higher on the first metatarsal/ medial arch while significantly less on the lateral metatarsals (p=.04). The percentage load on whole foot and forefoot was significantly less on standing (p=.01). Significant improvements were noted in the postoperative period, especially in the maximum foot surface area (p=.01), maximum and average foot loads, and improved weight transfers on lateral arch and forefoot (p=.02). The load on whole foot increased significantly from 46.1%±5.5% (preoperative) to 48.1%±5.5% (postoperative) and 49.9%±3.3% at follow-up (p=.01). CONCLUSIONThis is the first study using pedobarography to document altered foot pressure patterns during ambulation in patients with disc herniation and stenosis. Decreased load transfer, asymmetrical and unphysiological distribution of pressures on the affected foot were observed during weight bearing, which improved after surgical decompression.

Optimizing motor imagery BCI models with hard trials removal and model refinement

Deep learning models have demonstrated remarkable performance in the classification of motor imagery BCI systems. However, these models exhibit sensitivity to challenging trials, often called hard trials, leading to performance degradation. In this paper, we address this issue by proposing two novel methods for identifying and mitigating the impact of hard trials on model performance. The first method leverages model prediction scores to discern hard trials. The second approach employs a quantitative explainable artificial intelligence (XAI) approach, enabling a more transparent and interpretable means of hard trial identification. The identified hard trials are removed from the entire motor imagery training and validation dataset, and the deep learning model is further re-trained using the dataset without hard trials. To evaluate the efficacy of these proposed methods, experiments were conducted on the Open BMI dataset. The results for hold-out analysis show that the proposed quantitative XAI- based hard trial removal method has statistically improved the average classification accuracy of the baseline deep CNN model from 63.77% to 68.70%, with p-value = 7.66e−11 for the subject-specific MI classification. Additionally, analyzing the scalp map representing the average relevance scores of correctly classified trials compared to a misclassified trial provides a deeper insight into identifying hard trials. The results indicate that the proposed quantitaive-based XAI approach outperformes the prediction-score-based approach in hard trial identification.

Image-Based Approach Applied to Load Torque Estimation in Three-Phase Induction Motors.

This paper presents a novel method for load torque estimation in three-phase induction motors using air gap flux measurement and the conversion of this type of time-domain signal into grayscale images for further processing as inputs for an inception-type convolutional neural network. The magnetic flux was measured employing a Hall effect sensor installed inside the machine, near the stator slots, and above the stator windings. In this case, the sensor was able to measure a resultant magnetic flux density, having both rotor and stator magnetic flux contributions. The present methodology does not require motor parameters for torque prediction. The proposed approach successfully estimated load torque using three optimizers across almost the entire motor load operational range, spanning from 1.5% to 93.9% of the rated load. Four model configurations achieved a mean absolute percentage error (MAPE) less than or equal to 3.7%. Specifically, two models for a 40 × 50 pixel image achieved MAPE of 3.7% and 3%, one model for a 40 × 25 pixel image achieved a MAPE of 3.5%, and one model for a 50 × 80 pixel image achieved a MAPE of 3.3%. This research has been experimentally validated with a 7.5 kW squirrel cage induction machine.

Changes in Clinical and Network Functional Connectivity Parameters in Motor Networks and Cerebellum Based on Resting-State Functional Magnetic Resonance Imaging Data in Patients with Post-Stroke Hemiparesis Receiving Interactive Brain Stimulation Neurotherapy

Introduction. Interactive brain stimulation (IBS) neurotherapy is an advanced neurofeedback technology (NFB) that involves the organization of a feedback “target” based on signals recorded by functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). The NFB allows patients to volitionally self-regulate their current brain activity and may therefore be a useful treatment option for diseases with altered activation and functional connectivity (FC) patterns.
 Our objective was to assess the effects of IBS on the FC changes in motor networks and correlations between clinical and network parameters in patients with post-stroke hand paresis.
 Materials and methods. Patients with a history of stroke 2 months were randomized into a main group (n = 7) and a control group (n = 7). All the patients followed the stroke physical rehabilitation for 3 weeks. The main group received IBS training, where the patients learned to imagine movements of the paretic hand trying to amplify the fMRI signal from the primary motor cortex (M1) and the supplementary motor area (SMA) on the lesion side with simultaneous desynchronizing the μ- and β-2 EEG rhythms in the central leads. Clinical tests and MRI were performed prior to and immediately after the treatment. FC matrices were constructed using CONN software based on resting-state fMRI data.
 Results. By the end of the training, M1–M1 functional connectivity in the control group weakened, while no changes were observed in the main group. The FC strength was positively correlated with the grip strength (ρ = 0.69; p 0.01) and with the results of the Box and Blocks test (BBT score, ρ = 0.72; p 0.01) and the Fugl-Meyer assessment for upper extremity (FM-UE score, ρ = 0.87; p 0.005). Ipsilesional SMA connectivity with contralesional cerebellum weakened (p 0.05 in the main group). Its strength was negatively correlated with the BBT and FM-UE scores (both tests ρ = –0.44; p 0.05).
 Conclusions. Volitional control of M1 and SMA activity in the lesion hemisphere during the post-stroke IBS training alters the architecture of the entire motor network affecting clinically significant FC types. We studied a possible mechanism of this technology and its potential use in treatment programs.

A Comprehensive Analysis of the Reliability of Electric Vehicle Motor Systems: Exploring the Intricacies of Performance and Durability

Electric vehicles (EVs) have garnered significant attention in recent years due to their distinctive zero carbon emission capability. While their environmental advantages are widely acknowledged, concerns about the reliability of key components, particularly the drive motors and associated controllers, continue to linger. Previous studies have made strides in evaluating the reliability of individual drive motors in EVs. However, given the integrated nature of drive motors and motor controllers in EVs, a comprehensive assessment that considers both components as a unified system is imperative for more precise reliability forecasting. Furthermore, the multifaceted nature of drive motors and motor controllers, encompassing various components with diverse structures, types, and characteristics, can significantly influence the overall reliability of the motor system. Unfortunately, these nuances have often been overlooked in prior research, creating a knowledge gap that needs to be addressed. To address this gap, our study offers a holistic investigation into the reliability of the entire motor system in pure electric vans, which includes both the drive motors and motor controllers. We initiate our research by employing theoretical models to predict the failure rates of individual subassemblies and components within the drive motor and motor controller. Building upon these predictions, we conduct an in-depth assessment of the overall motor system reliability. Our findings reveal the vulnerabilities associated with specific subassemblies and components within the motor system, offering critical insights that challenge some of the prevailing assumptions in existing reliability research. These insights are instrumental in guiding future advancements in reliability design and maintenance practices tailored for pure electric vans. The adoption of EVs continues to grow, driven by their environmental benefits and expanding market share, it becomes increasingly crucial to address concerns related to the reliability of essential components like drive motors and control systems. While previous research has largely focused on component-level reliability, our study adopts a more comprehensive approach, evaluating the entire motor system. Through a combination of theoretical modeling and empirical analysis, we aim to provide a robust framework for predicting failure rates and enhancing the overall reliability of EV motor systems. By uncovering vulnerabilities and potential areas for improvement, this research offers valuable insights to advance the design, development, and maintenance of reliable electric vehicles.

An Exhaustive Examination of the Motor System’s Reliability in Electric Vehicles

Due to their unique zero carbon emission feature, electric vehicles (EVs) have garnered increasing interest in recent years. However, concerns persist regarding their reliability, particularly concerning critical components. Efforts have been made to assess the reliability of drive motors in EVs. Yet, given the integration of drive motors and motor controllers as a single system in EVs, a combined assessment is essential for a more accurate reliability prediction. Additionally, considering the multiple components within both drive motors and motor controllers, their structure, type, and characteristics may influence the overall reliability of the motor system, a factor overlooked in previous research. To bridge this knowledge gap, this study investigates the reliability of the entire motor system in pure electric vans, encompassing both drive motors and motor controllers. The research begins with predicting the theoretical failure rates of subassemblies and components within the drive motor and motor controller. Subsequently, based on these predictions, the reliability of the entire motor system is assessed. The findings highlight vulnerable subassemblies and components within the motor system, shedding light on potential shortcomings in existing reliability research. These new insights are deemed crucial for informing future reliability design and maintenance practices for pure electric vans. This study undertakes an exhaustive investigation into the reliability of the motor system in EVs. As EVs gain prominence for their environmental benefits and increasing market share, concerns regarding the reliability of critical components, such as the drive motor and associated control systems, become paramount. While prior research has addressed component-level reliability, this study takes a holistic approach by assessing the entire motor system. Through theoretical modeling and empirical analysis, the study predicts failure rates of subassemblies and components within the drive motor and control systems, culminating in an evaluation of the overall motor system reliability. By uncovering vulnerabilities and potential areas for improvement, this research offers valuable insights to advance the design, development, and maintenance of reliable electric vehicles.

Effect of the period of EEG signals on the decoding of motor information.

Decoding movement information from electroencephalogram to construct brain-computer interface has promising applications. The EEG data during the entire motor imagery (MI) period or movement execution (ME) period is generally decoded, and calculation of numerous information and massive dataset is time-consuming. In order to improve decoding efficiency, the joint topographic maps of the brain activation state of 15 subjects were studied during different periods. The results showed that the activation intensity of the preparation period in the motor imagery experiment was higher than during the exercise period, while during the exercise period, the activation intensity was higher than in the preparation period in the movement execution experiment. Hence, the wavelet neural network was used to decode the six-class movements including elbow flexion/extension, forearm pronation/supination and hand open/close in periods of MI/ME. The experimental results show that the accuracy obtained in the preparation period is the highest in the motor imagery experiment, which is 80.77%. On the other hand, the highest accuracy obtained in the exercise period of the movement execution experiment is 79.26%. It further proves that the optimized period is a key decoding factor to reduce the cost of calculation, and this new decoding method is effective to build a more intelligent brain-computer interface system.

Laser-induced selective metallization of epoxy resin: Preparing ultra-thin and ultra-light motors

Epoxy composites with an excellent laser-induced selective metallization (LISM) capability were designed and prepared by combining the bisphenol A-type epoxy resin (EP) with laser sensitizers (CuO·Cr2O3 and ATO). The dispersion of laser sensitizers in epoxy molding compound (EMC), as well as their influence on the curing reaction and mechanical strength of epoxy composites, was investigated. We confirmed that CuO·Cr2O3 is the more suitable laser sensitizer for epoxy composites. The tensile strength of EP/CuO·Cr2O3 composite was 51.6 MPa, and the resistance of the obtained copper layers was 0.2 Ω. Moreover, this composite can be used to produce ultrafine copper wires and perforated circuits using LISM technology. Inspired by its excellent LISM performance, an ultra-thin and ultra-light motor was designed and fabricated. The weight of the entire motor was only 28.8 g and a thickness of 6 mm due to the integration of the stator frame and stator windings.

Enhancing Electric Vehicle Reliability and Integration with Renewable Energy: A Multi-Faceted Review

Electric vehicles (EVs) are gaining attention due to their zero carbon emissions, but concerns about their reliability, especially critical components, persist. Previous research has primarily focused on EV drive motor reliability, neglecting the motor controller. To address this gap, this study assesses the reliability of the entire motor system in electric vans, including both drive motor and motor controller components. It predicts failure rates for these components, highlighting vulnerabilities and shortcomings in existing research, which can inform future design and maintenance. In addition, the integration of EVs and renewable energy resources has garnered attention, but concerns about component reliability have arisen. A novel approach called " Innovative Incentive-Driven Fuzzy Fault Tree Analysis " (IIFFTA) is introduced for power systems incorporating EVs and renewable energy, addressing vague and imprecise events and data deficiencies in conventional fault tree analysis. IIFFTA considers different component failure rates and probability values of fault occurrences, offering a more effective risk assessment method. Lastly, plug-in electric vehicles (PEVs) impact distribution systems, and this paper explores distribution feeder reconfiguration (DFR) as a reliability-enhancing strategy for coordinating vehicle-to-grid (V2G) services from PEV fleets within a stochastic framework. The study accounts for uncertainties related to network demand, energy prices, wind power generation, and PEV fleet behavior, employing a self-adaptive evolutionary algorithm (SOS) to address the stochastic optimization problem.

Postural control measured before and after simulated ankle inversion landings among individuals with chronic ankle instability, copers, and controls

BackgroundPostural control measured during single-leg stance and single-leg hop stabilization has been used to estimate sensorimotor function in CAI individuals and copers. To date, studies have not used postural control tasks as a way of measuring responses to sudden changes in sensory information after simulated ankle inversion landings. Research questionA cross-sectional study was performed to identify any differences in static and dynamic postural control before and after simulated ankle inversion landings among individuals with chronic ankle instability (CAI), copers, and healthy controls. MethodsNineteen CAI individuals, 19 copers, and 19 controls participated in this study. Participants performed 3 static and dynamic balance tasks before and after simulated ankle inversion landings onto a 25° tilted platform from a height of 30 cm. The main outcome measures were the center of pressure (COP) velocity and range from the single-leg stance, as well as the dynamic postural stability index from the single-leg hop stabilization. The Wilcoxon signed-rank test was used to compare posttest and pretest differences in static and dynamic postural control between groups. ResultsIn the static postural control measures, the CAI group had a higher difference in COP velocity and COP range in the frontal plane (p < 0.05 and p < 0.05, respectively) than the coper group. In the dynamic postural control measures, the CAI group demonstrated a higher difference in the vertical stability index (p < 0.05) than the healthy control group. SignificanceCAI individuals have persistent worse postural control after somatosensory modulation due to their inability to adapt to sudden somatosensory modulation. Relative to CAI individuals, copers may have different abilities not only the integration of somatosensory input about ankle inversion modulation, but also the adaptation of the entire motor control system, preventing recurrent ankle sprains after an initial LAS. Therefore, somatosensory modulation may be the indicator of understanding CAI and coper.

Thermal-Hydraulic Modeling of Oil-Immersed Motor Pump

The integrated design of the motor and axial piston pump eliminates the coupling structure, resulting in a compact and lightweight motor-pump structure. The challenge of motors overheating has always been a major concern. To address this issue, the hydraulic oil throughout the motor pump is utilized for cooling the high-speed motor, effectively improving the power density and heat dissipation capability of the hydraulic power unit. This integrated design approach has successfully resolved the significant issue of overheating motors, leading to enhanced performance of the hydraulic power unit. To address this concern, the entire motor pump’s oil is utilized to cool the high-speed motor. Consequently, the thermodynamic prediction of high-speed motor pumps has become increasingly important. In this study, the impact of motor heat generation on hydrodynamics is analyzed, and the heat transfer of the motor pump is investigated using the control volume method. Furthermore, thermodynamic models of hysteresis loss, eddy current loss, alternating current loss, churning loss, and throttling loss are established for the oil-immersed motor pump. The change in oil viscosity is also considered. The instantaneous temperature change rule of the oil within the oil-immersed motor pump is derived. Additionally, the influence of various working conditions such as pressure and speed on the temperature of the motor pump’s key node is examined. The experimental results indicate the accuracy of the thermodynamic calculation, and the significant effect of motor loss on the leakage temperature.

Evaluation of the Effect of Intravenous Dexamethasone on the Duration of Spinal Anaesthesia in Parturients Undergoing Lower Segment Caesarean Section.

Introduction Dexamethasone is shown to prolong the duration of nerve blocks when administered perineurally as well as intravenously. The effect of intravenous dexamethasone on the duration of hyperbaric bupivacaine spinal anesthesia is lesser known. We conducted a randomized control trial to determine the effect of intravenous dexamethasone on the duration of spinal anesthesia in parturients undergoing lower-segment cesarean section (LSCS). Methods Eighty parturients planned for LSCS under spinal anesthesia were randomly allocated to two groups. Patients in group A were administered dexamethasone intravenously, and group B received normal saline intravenously before spinal anesthesia. The primary objective was to determine the effect of intravenous dexamethasone on the duration of sensory and motor block after spinal anesthesia. The secondary objective was to determine the duration of analgesia and complications in both groups. Result The total duration of the sensory and motor blocks in group A was 118.38 ± 19.88 minutes and 95.63 ± 19.91 minutes, respectively. The entire sensory and motor blockade duration in group B was 116.88 ± 13.48 minutes and 97.63 ± 15.15 minutes, respectively. The difference between the groups was found to be statistically insignificant. Conclusion Intravenous 8 mg dexamethasone in patients planned for LSCS under hyperbaric spinal anesthesia does not prolong the sensory or motor block duration compared to placebo.

A Fast Numerical Modeling Approach Based on Boundary Field Method for Calculating AC Losses in Superconducting Motors

To improve the computational efficiency of the numerical methods for calculating ac loss in HTS motor, a new method called ‘Boundary field method’ is proposed in this article. This method combines the strength of ANSYS and COMSOL, which can reduce the complexity of modeling and computation time. In this article, three finite-element method based models, as case studies, were developed for a 100-kW superconducting induction motor. Model A models entire motor in COMSOL using A-H formulation, considering nonlinear <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E–J</i> relationship of high temperature superconducting tapes, which can calculate ac loss of motor directly; Combining another two models: Model B (the same entire superconducting motor in ANSYS) and model C (only superconducting stator windings in COMSOL) can achieve new method for calculating ac loss. The AC loss calculation error between two methods for two-layer windings in one slot is 2.5% and 7%, respectively. These results conclude the effectiveness and accuracy of “boundary field method.” More importantly, the computation time reduces dramatically from 48 hours in Model A to only 2 hours for proposed approach. This accurate and computationally efficient new numerical modeling approach could be used to calculate ac loss in various types of superconducting applications in future.

Perspectives on Electric Motor Market Transformation for a Net Zero Carbon Economy

Energy efficiency is one of the most powerful strategies to mitigate the impacts of climate change by reducing energy demand, which in turn reduces the emissions of Green House Gases (GHG), as well as reducing the burden on the supply side renewable generation expansion. Because electric motors systems represent such a large share of the overall electricity consumption (over 50%), large savings potential could be made available by the use of energy-efficient motor systems both in new installations and by accelerating the replacement of old inefficient motors. Since electric motors are very reliable, their lifetime is long (according to recent studies it may exceed 20 years) which translates into a very inefficient existing stock despite worldwide policy efforts. This paper analyzes the current efficiency of the installed stock and the causes for its low efficiency, possible policy options to increase its the efficiency, the role of new technologies and improvements possible by targeting the entire motor system at the time of motor replacement. The paper presents an innovative analysis of the estimated impact of increasing the uptake of high-efficiency motors and motor systems; effective policies could translate into 100 TWh/year in the European Union if additional measures, such as addressing oversizing, proper controls (VSDs) and digitisation, are also implemented. If similar measures were adopted globally, the savings triggered could be at least tenfold reaching over 1000 TWh/year.

Flexor hallucis brevis motor unit behavior in response to moderate increases in rate of force development.

Studies on motor unit behaviour with varying rates of force development have focussed predominantly on comparisons between slow and ballistic (i.e., very fast) contractions. It remains unclear how motor units respond to less extreme changes in rates of force development. Here, we studied a small intrinsic foot muscle, flexor hallucis brevis (FHB) where the aim was to compare motor unit discharge rates and recruitment thresholds at two rates of force development. We specifically chose to investigate relatively slow to moderate rates of force development, not ballistic, as the chosen rates are more akin to those that presumably occur during daily activity. We decomposed electromyographic signals to identify motor unit action potentials obtained from indwelling fine-wire electrodes in FHB, from ten male participants. Participants performed isometric ramp-and-hold contractions from relaxed to 50% of a maximal voluntary contraction. This was done for two rates of force development; one with the ramp performed over 5 s (slow condition) and one over 2.5 s (fast condition). Recruitment thresholds and discharge rates were calculated over the ascending limb of the ramp and compared between the two ramp conditions for matched motor units. A repeated measures nested linear mixed model was used to compare these parameters statistically. A linear repeated measures correlation was used to assess any relationship between changes in recruitment threshold and mean discharge rate between the two conditions. A significant increase in the initial discharge rate (i.e., at recruitment) in the fast (mean: 8.6 ± 2.4 Hz) compared to the slow (mean: 7.8 ±2.3 Hz) condition (P = 0.027), with no changes in recruitment threshold (P = 0.588), mean discharge rate (P = 0.549) or final discharge rate (P = 0.763) was observed. However, we found substantial variability in motor unit responses within and between conditions. A small but significant negative correlation (R2 = 0.33, P = 0.003) was found between the difference in recruitment threshold and the difference in mean discharge rate between the two conditions. These findings suggest that as force increases for contractions with slower force development, increasing the initial discharge rate of recruited motor units produces the increase in rate of force development, without a change in their recruitment thresholds, mean or final discharge rate. However, an important finding was that for only moderate changes in rate of force development, as studied here, not all units respond similarly. This is different from what has been described in the literature for ballistic contractions in other muscle groups, where all motor units respond similarly to the increase in neural drive. Changing the discharge behaviour of a small group of motor units may be sufficient in developing force at the required rate rather than having the discharge behaviour of the entire motor unit pool change equally.

Design and Performance Analysis of a Bioelectronic Controlled Hybrid Serial-Parallel Wrist Exoskeleton.

Wrist exoskeletons are increasingly being used in the rehabilitation of stroke and hand dysfunction because of its ability to assist patients in high intensity, repetitive, targeted and interactive rehabilitation training. However, the existing wrist exoskeletons cannot effectively replace the work of therapist and improve hand function, mainly because the existing exoskeletons cannot assist patients to perform natural hand movement covering the entire physiological motor space (PMS). Here, we present a bioelectronic controlled hybrid serial-parallel wrist exoskeleton HrWr-ExoSkeleton (HrWE) which is based on the PMS design guidance, the gear set can carry out forearm pronation/supination (P/S) and the 2-DoF parallel configuration fixed on the gear set can carry out wrist flexion/extension (F/E) and radial/ulnar deviation (R/U). This special configuration not only provides enough range of motion (RoM) for rehabilitation training (85F/85E, 55R/55U, and 90P/90S), but also makes it easier to provide the interface for finger exoskeletons and be adapted to upper limb exoskeletons. In addition, to further improve the rehabilitation effect, we propose a HrWE-assisted active rehabilitation training platform based on surface electromyography signals.

Analysis of Torsional Vibrations on the Resolver Under Eccentricity in PMSM Drive System

Since any error in the rotor angle caused by the resolver affects the entire permanent magnet synchronous motor (PMSM) control drive system, it is necessary to investigate its effect on mechanical vibrations. Torsional vibration is accordingly considered in the following study. Thereby, first, the effect of resolver errors on the harmonic content of motor current and, subsequently, torque ripple (TR) was investigated. Then, dynamical modeling is done for the generator–motor–resolver set to get the mechanical frequency response (FR) resulting from the resolver errors. Based on the above modeling, the dynamic equations (DEQs) of the system were derived, and the mechanical characteristics of the set, including natural frequency values and mode shapes, were extracted. Thereafter, TR was employed in the DEQs, and the mechanical FR caused by the resolver error was obtained. Eventually, comparing mechanical FR with electrical FR was done according to diagnosis superiority. All analyses were done using experimentally verified models.

FP.10 Combination of BIO101 with antisense oligonucleotide therapy demonstrates synergistic beneficial effects in severe SMA-like mice

Spinal Muscular Atrophy (SMA) is a neurodegenerative disease characterized by the loss of spinal motor neurons and progressive muscular atrophy, due to insufficient level of survival of motor neuron protein (SMN). SMA is defined as a non-cell autonomous disease, involving numerous tissues and cell-types, including skeletal muscles. In this context, strategies to overexpress SMN protein and approaches to maintain neuromuscular functions are currently developed and appear as promising long-term prospect for therapy in SMA. We evaluated the efficacy of Sarconeos (API BIO101), a Mas receptor activator, as monotherapy and in combination with ASO therapy in severe SMA-like mice (Smn^Δ7/Δ7; 2 copies SMN2^+/−). We showed beneficial effects of BIO101 as monotherapy on the entire motor unit with a complete protection of lumbar motor neurons, a limited muscular atrophy (-17% in the tibialis, -40% in the plantaris, and -12% in the soleus), an increased vascularization (+10% in the tibialis and the plantaris, +3% in the soleus), and an accelerated maturation of both muscular fibers and neuromuscular junctions. Interestingly, these benefits were independent of SMN expression. In combination with ASO therapy, BIO101 demonstrated synergistic effects on body weight (+1% with BIO101, +11% with ASO, +32% with ASO + BIO101 at 10 days after birth compared to vehicle) and increased survival (+5 days of median survival). Most importantly, the co-treated SMA-like mice improved their moving capacity (+40%) and their fatigue resistance (4,2-fold) compared to SMA-like mice treated only with ASO. These results provide strong evidence that BIO101, with beneficial effects on the entire motor unit, constitutes an efficient SMN-expression-independent therapy for improving muscle function and should be considered as a potential combinatorial option for a new therapeutic strategy in SMA patient.

Motor Network Reorganization Induced in Chronic Stroke Patients with the Use of a Contralesionally-Controlled Brain Computer Interface

ABSTRACT Upper extremity weakness in chronic stroke remains a problem not fully addressed by current therapies. Brain–computer interfaces (BCIs) engaging the unaffected hemisphere are a promising therapy that are entering clinical application, but the mechanism underlying recovery is not well understood. We used resting state functional MRI to assess the impact a contralesionally driven EEG BCI therapy had on motor system functional organization. Patients used a therapeutic BCI for 12 weeks at home. We acquired resting-state fMRI scans and motor function data before and after the therapy period. Changes in functional connectivity (FC) strength between motor network regions of interest (ROIs) and the topographic extent of FC to specific ROIs were analyzed. Most patients achieved clinically significant improvement. Motor FC strength and topographic extent decreased following BCI therapy. Motor recovery correlated with reductions in motor FC strength across the entire motor network. These findings suggest BCI-mediated interventions may reverse pathologic strengthening of dysfunctional network interactions.