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Several computational models make predictions about the activation states of individual elements of an action sequence during planning and execution; however, the neural mechanisms of action planning are still poorly understood. Simple chaining models predict that only the first response in an action sequence should be active during planning. Conversely, some parallel activation models suggest that during planning, a serial inhibition process places the individual elements of the action into a serial order across a winner-takes-all competitive choice gradient in which earlier responses are more active, and hence likely to be selected for execution compared with later responses. We triggered transcranial magnetic stimulation pulses at 200 or 400 ms after the onset of a five-letter word, in which all but one response was planned and typed with the left hand, except for a single letter which required a right index finger response exclusively at one of five serial positions. We measured the resulting motor-evoked potentials at the right index finger as a marker for the activation state of that planned response. We observed no difference in motor-evoked potential amplitude across any serial position when a right index finger response was planned at 200 ms after the onset of the word; however, we observed a graded pattern of activation at 400 ms, with earlier positions that required a right index finger response showing greater motor-evoked potentials amplitude compared with later positions. These findings provide empirical support for competitive queuing computational models of action planning. [ABSTRACT FROM AUTHOR]

We develop a rotary motor to reduce backward motion in stick–slip with an active clamp mechanism. Backward motion refers to the undesired movement observed when operating a rotary stick–slip motor powered by a piezoelectric actuator under actual conditions, where the rotor rotates in the opposite direction to the intended rotation. This could cause imprecision and inaccurate motion. The conventional stick–slip motor relies on contact with the rotor to induce rotation. The proposed active clamp mechanism adjusts the contact distance with the rotor, ensuring contact is maintained only when the rotor is rotating. This helps reduce backward motion. Additionally, implementing this mechanism using the conventional method requires one stick–slip module for rotation and two inchworm drive modules for clamping. In contrast, the proposed mechanism consists of a single module each for the driving actuator and clamping actuator. A preliminary model with a dimension of 34 × 27 mm was constructed for experimentation. Through the experiments, it was confirmed that the proportion of backward motion relative to the initial movement in one step decreased by approximately 20%. Furthermore, with the reduction in backward motion, the rotational displacement per step was confirmed to improve by about twice, increasing from 17 to 33 millidegrees. [ABSTRACT FROM AUTHOR]

High temperature superconductors (HTSs) are enablers of extensive electrification for aircraft propulsion. Indeed, if used in electrical machines, HTS materials can drastically improve their performance in terms of the power-to-weight ratio. Among the different topologies of superconducting electrical machines, a flux modulation machine based on HTS bulks is of interest for its compactness and light weight. Such a machine is proposed in the FROST (Flux-barrier Rotating Superconducting Topology) project led by Airbus to develop new technologies as part of their decarbonization goals driven by international policies. The rotor of the machine will house large ring-segment-shaped HTS bulks in order to increase the output power. However, the properties of those bulks are scarcely known and have barely been investigated in the literature. In this context, the present work aims to fill out partially this scarcity within the framework of FROST. Thus, a thorough characterisation of the performances and homogeneity of 11 large REBaCuO bulks was carried out. Ten of the bulks are to be utilized in the machine prototype, originally keeping the eleventh bulk as a spare. A first set of characterisation was conducted on the eleven bulks. For this set, the trapped field mapping and the critical current were estimated. Then, a series of in-depth characterisations on the eleventh bulk followed. It included critical current measurement, X-ray diffraction, and scanning electron microscopy on different millimetre-size samples cut out from the bulk at various locations. The X-ray diffraction and scanning electron microscopy showed weakly oxygenated regions inside the bulk explaining the local drop or loss in superconducting properties. The objective was to determine the causes of the inhomogeneities found in the trapped field measured on all the bulks, sacrificing one of them, here the spare one. To help obtain a clearer picture, a numerical model was then elaborated to reproduce the field map of the eleventh bulk using the experimental data obtained from the characterisation of its various small samples. It is concluded that further characterisations, including the statistics on various bulks, are still needed to understand the underlying reasons for inhomogeneity in the trapped field. Nonetheless, all the bulks presented enough current density to be usable in the construction of the proposed machine. [ABSTRACT FROM AUTHOR]

The stability of the robot's performance is very important, especially for the wheeled mobile robots that use swerve drives, which need kinematic control to reach the destination point. The study of robot movement known as kinematics is based on an examination of the geometric structure of the robot, with no consideration given to the mass, force, or acceleration that the robot experiences during movement. This study aims to model and simulate the kinematic control design of a wheeled robot that uses a swerve drive. This robot uses BLDC motor actuator so that the robot can reach its destination very quickly and steadily. The test is carried out by simulating and comparing the performance response using BLDC motors and DC motors. According to the testing and trials, the robot can reach its destination by modeling its kinematic control, and BLDC motors are found to be more reliable and efficient for driving and steering than DC motors. [ABSTRACT FROM AUTHOR]

This study focuses on the motor fault diagnosis facing the long-tailed distribution data, characterized by a multitude of fault types with limited data per category and the healthy state with massive data. This skewed distribution makes the traditional diagnostic models fail to identify less frequent faults. To this end, we introduce a novel fault diagnosis model, named Transformer- and gated-recurrent unit (GRU)-based network (TransGRU), to improve the diagnosis accuracy with the long-tailed distribution data. The TransGRU has two main modules, i.e. the feature extraction module and the correction module. The former is based on the Informer encoder with ProbSparse self-attention to extract features from the long-range multi-sensor data. The latter employs the GRU network addressing the long-tail effect by adjusting the diagnosis results via the gate mechanism. Besides, we informatively design an adaptive-conditional loss (ACL) function for the long-tailed fault diagnosis by integrating the properties of focal loss, class-tailored weights, and confusion weights. ACL concentrates on challenging classifications while balancing the representation and significance of various fault modes. Validation on experimental motor data confirms the capability of our TransGRU in identifying a wide range of fault types with limited fault data compared with the Transformer and state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Emerging research suggests that music and rhythm-based interventions offer promising avenues for facilitating functional outcomes for autistic individuals. Evidence suggests that many individuals with ASD have music processing and production abilities similar to those of neurotypical peers. These individual strengths in music processing and production may be used within music therapy with a competence-based treatment approach. We provide an updated perspective of how music and rhythm-based interventions promote sensory and motor regulation, and how rhythm and music may then impact motor, social, and communicative skills. We discuss how music can engage and motivate individuals, and can be used intentionally to promote skill acquisition through both structured and flexible therapeutic applications. Overall, we illustrate the potential of music and rhythm as valuable tools in addressing skill development in individuals on the autism spectrum. [ABSTRACT FROM AUTHOR]

Evaluations of treatment efficacy in Duchenne muscular dystrophy (DMD), a rare genetic disease that results in progressive muscle wasting, require an understanding of the 'meaningfulness' of changes in functional measures. We estimated the minimal detectable change (MDC) for selected motor function measures in ambulatory DMD, i.e., the minimal degree of measured change needed to be confident that true underlying change has occurred rather than transient variation or measurement error. MDC estimates were compared across multiple data sources, representing >1000 DMD patients in clinical trials and real-world clinical practice settings. Included patients were ambulatory, aged ≥4 to <18 years and receiving steroids. Minimal clinically important differences (MCIDs) for worsening were also estimated. Estimated MDC thresholds for >80% confidence in true change were 2.8 units for the North Star Ambulatory Assessment (NSAA) total score, 1.3 seconds for the 4-stair climb (4SC) completion time, 0.36 stairs/second for 4SC velocity and 36.3 meters for the 6-minute walk distance (6MWD). MDC estimates were similar across clinical trial and real-world data sources, and tended to be slightly larger than MCIDs for these measures. The identified thresholds can be used to inform endpoint definitions, or as benchmarks for monitoring individual changes in motor function in ambulatory DMD. [ABSTRACT FROM AUTHOR]

In order to evaluate the influences of the topology design of a Halbach Magnet Array (HA) on the performance of a motor, a PMSM with an outer coreless rotor using a Halbach Magnet Array (HAORPMSM) is proposed in this article. The design parameters of the HA could be separated into dividing methods per pole, magnet thickness, and initial magnetization direction angle. The phase Back-EMF under constant mechanical speed is chosen as the index to measure the performance of the motor. To start with, different dividing methods of the HA are evaluated. After that, the influence of thickness considering the utilization of the magnet is studied. Lastly, the relationship between initial magnetization direction and motor manufacturing is represented. The results show that the HA design meets the optimized performance considering the balance of the amount of magnet usage and manufacturing when using specific HA parameters. [ABSTRACT FROM AUTHOR]

The cholinergic system plays a key role in motor function, but whether pharmacological modulation of cholinergic activity affects motor sequence learning is unknown. The acetylcholine receptor antagonist biperiden, an established treatment in movement disorders, reduces attentional modulation, but whether it influences motor sequence learning is not clear. Using a randomized, double‐blind placebo‐controlled crossover design, we tested 30 healthy young participants and showed that biperiden impairs the ability to learn sequential finger movements, accompanied by widespread oscillatory broadband power changes (4–25 Hz) in the motor sequence learning network after receiving biperiden, with greater power in the theta, alpha and beta bands over ipsilateral motor and bilateral parietal–occipital areas. The reduced early theta power during a repeated compared with random sequence, likely reflecting disengagement of top‐down attention to sensory processes, was disrupted by biperiden. Alpha synchronization during repeated sequences reflects sensory gating and lower visuospatial attention requirements compared with visuomotor responses to random sequences. After biperiden, alpha synchronization was greater, potentially reflecting excessive visuospatial attention reduction, affecting visuomotor responding required to enable sequence learning. Beta oscillations facilitate sequence learning by integrating visual and somatosensory inputs, stabilizing repeated sequences and promoting prediction of the next stimulus. The beta synchronization after biperiden fits with a disruption of the selective visuospatial attention enhancement associated with initial sequence learning. These findings highlight the role of cholinergic processes in motor sequence learning. [ABSTRACT FROM AUTHOR]

The hub motor-driven mobile platform has gradually replaced the traditional centralized electric drive system. There is ever-increasing demand for flowers, fruits, vegetables, and tea horticulture for the new energy-powered operating equipment, particularly with high efficiency, energy saving, compact structure, independent and controllable advantages. Compared with direct-drive hub motors, the geared hub motors have been the mainstream of the drive unit for facility horticulture, due to the higher overload and torque output. The operational requirements of large load and torque can be fully met in the operation scenarios of facility horticulture. However, the geared hub motors are limited to the size of the space inside the hub. The high heat generation has seriously restricted the operational performance of electric drive mobile platforms. In this study, a decelerated inner-rotor axial flux hub motor was designed to meet the requirements of the low-speed and high-torque traction for electric-driven mobile platforms in facility horticulture operation scenarios. The electromagnetic finite element (FE) model was established to analyze the electromagnetic and loss features of the hub motor. Moreover, an improved magnetic-thermal coupling FE model of the hub motor was also constructed using the thermal network. The effect of temperature on the winding resistivity was considered to reduce the prediction accuracy of the simulation model, compared with the conventional magnetic-thermal bidirectional model. The prediction accuracy of the torque was improved by 5.33% using the improved model, compared with the bench tests. The correctness of the model was verified using the magnetic-thermal coupling FE model. A systematic investigation was made on the influence of the temperature and phase current on the torque of the motor. The experiments were also conducted on the external efficiency of the hub motor under peak operating conditions. The simulation results reveal that the average output torque of the motor decreased, as the steady-state temperature increased. The prediction value of torque was deviated by less than 1.56% from the measured at the motor speed of 800 r/min. The output torque of the motor also decreased with increasing motor temperature. The output torque of 15.23 N·m was reduced by 7.66% at the current of 32 A, compared with the conventional. The experimental results demonstrate that the power of the hub motor increased with the increase of the rotational speed in the middle and low-speed ranges. The peak power was up to 4.59 kW, while the torque almost remained constant. The output torque also decreased with the increase of motor temperature. The average output torque of the motor was linearly related to the phase current in the range of 0 to 20 A. The efficiency of the motor was up to 93.2% in the middle speed range with the torques in the range of 300 to 600 N·m. This finding can provide a direct guideline for the structural design of hub motors and the magnetic-thermal multi-physical field coupling performance analysis. [ABSTRACT FROM AUTHOR]

We propose an inhibitory control system for downhill turning by using a pre-installed friction brake mounted on a manual wheelchair. The braking force of the wheel is controlled by an added DC geared motor that pulls the brake wire in accordance with the ground angle. The proposed automatic braking system can reduce unexpected turns on downhill slopes. The proposed control system is also designed to be installed as an add-on device for manual wheelchairs. The effectiveness of the proposed system is verified using a wheelchair through a slope running experiments. [ABSTRACT FROM AUTHOR]

Along with the rising popularity of pay-as-you-go cloud services, many businesses and communities are deploying their business or scientific workflow applications on cloud-based computing platforms. The primary responsibility of cloud service providers is to reduce the monetary cost and execution time of Infrastructure as a Service (IaaS) cloud services. The majority of current solutions for cost and makespan reduction were developed for conventional cloud platforms and are incompatible with heterogeneous computing systems (HCS) having service-based resource management approaches and pricing models. Fog-cloud infrastructures (FCI) have emerged as desirable target areas for workflow automation across several fields of application. In heterogeneous FCI, the execution of workflows involving tasks having different properties might influence the performance in terms of resource usage. The primary goal of this research is to efficiently offload the computational task and optimally schedule the workflow in such diverse computing environment. In this article, we present a novel strategy for building an environment that includes techniques for offloading and scheduling while balancing competing demands from the user and the resource providers. In order to address the issue of uncertainty, our approach incorporates a fuzzy dominance-based task clustering and offloading technique. To construct a suitable execution sequence of tasks that helps to limit the precedence relationship, by preserving dependency constraints among the tasks, a novel algorithm for tasks segmentation is employed. To simplify the problem of the complexity, a hybrid-heuristics based on Harmony Search Algorithm (HSA) and Genetic Algorithm (GA) for resource scheduling algorithm is used. The multi-objective optimization using three competing objectives is taken into consideration for investigation in heterogeneous FCI. The fitness function derived includes minimization of makespan and cost along with maximization of resource utilization. We performed experimental research using five workflow datasets in order to investigate and verify the efficacy of our proposed technique. We contrasted our proposed strategy with the primary, closely comparable strategies. Extensive testing using scientific workflows confirms the effectiveness of our offloading approach. Our solution provided a substantially better cost-makespan tradeoffs, while achieving significantly less energy consumption and can execute marginally quicker than the existing algorithms. [ABSTRACT FROM AUTHOR]

Bilateral movement has been reported to enhance actual motor performance more than unilateral movement and increase motor cortex activation more than unilateral movement. We hypothesized that bilateral motor imagery would result in greater improvements in event-related desynchronization (ERD) amplitude and ball rotation performance than unilateral motor imagery. Forty healthy young adults participated in this study. The mental practice session was performed in the unilateral hand condition (right and left hands) and bilateral hand condition for four blocks. ERD in mental practice was calculated using electroencephalography (EEG). The ball rotations were compared between the pre-and post-tests of mental practice. The results showed a greater improvement in actual motor performance with unilateral motor imagery than with bilateral motor imagery. ERD analysis showed no significant differences in multiple comparisons. These results did not support this hypothesis. Nonetheless, the present study showed that unilateral movements resulted in greater performance gains than bilateral movements, suggesting that bilateral motor imagery may have additional control processes similar to actual movements. [ABSTRACT FROM AUTHOR]

The increasing demand for sustainable development and energy efficiency underscores the importance of optimizing motors in driving the upgrade of energy structures. This paper studies a data-driven approach for the multi-objective optimization of motors designed for scenarios involving multiple variables, objectives, and limited sample sizes and validates its efficacy. Initially, sensitivity analysis is employed to identify potentially influential variables, thus selecting key design parameters. Subsequently, Latin hypercube sampling (LHS) is utilized to select experimental points, ensuring the coverage of the modeled test points across the experimental space to enhance fitting accuracy. Finally, the support vector regression (SVR) algorithm is employed to fit the objective function, in conjunction with multi-objective particle swarm optimization (MOPSO) for solution derivation. The presented method is used to optimize the efficiency, average output torque, and induced electromotive force harmonic distortion rate of a permanent magnet synchronous motor (PMSM). The results show an improvement of approximately 6.80% in average output torque and a significant decrease of about 59.5% in the induced electromotive force harmonic distortion rate, with minimal impact on efficiency. This study offers a pathway for enhancing motor performance, holding practical significance. [ABSTRACT FROM AUTHOR]

This paper explores the applicability of cryogenic permanent magnet motor stator materials for LNG pumps. First, this study selected four kinds of silicon steel sheets for motor stators tested at room temperature and ultra-low temperature and obtained the magnetization characteristics and loss characteristics of the four silicon steel sheets at room temperature and ultra-low temperature. Then, through a comparative analysis of experimental data, the applicability of silicon steel sheet material in an ultra-low-temperature environment was verified. Finally, the improved methods of the basic iron loss model of silicon steel sheets and the basic iron loss model of motors were proposed, and the accuracy and feasibility of the improved models were verified. [ABSTRACT FROM AUTHOR]

AC-DC-AC traction transmission system provides power for high-speed train and is one of the key technologies for rail transit. The rectifier part adopts a four-quadrant rectifier, which has advantages such as high power factor, low harmonic content, and energy feedback. However, due to the power characteristics of single-phase power supply in electrified railways, there is a double power frequency fluctuation in the DC link voltage of the traction transmission system. In addition, the current output controlled by the inverter contains higher-order harmonics. In order to study the influence of harmonic components on the traction motor of high-speed train, an AC-DC-AC traction system simulation model for high-speed train was established. The results show that after LC filtering, at the condition that the stator current frequency is close to 100Hz, the motor stator current still undergoes distortion, but the effect on torque is not significant. When the LC filter fails, the torque ripple caused by 100Hz is very significant. It is recommended to consider this in the fault detection system of the traction transmission system. During train operation, the torque ripple at frequency of 6-times motor stator current is prominent, and this frequency also exists in the voltage and current of the DC link. [ABSTRACT FROM AUTHOR]

Objective: To estimate the associations between height, weight, and three estimates of skeletal age (SA) and the strength and motor performance of male soccer players in two chronological age (CA) groups, 9–12 (n = 60) and 13–16 (n = 52) years. Methods: Height, weight, strength (grip), speed (5 m, 20 m sprints), acceleration (time at crossing 10 m in 20 m sprint), agility (figure‐of‐eight run), power (vertical jump), and endurance (intermittent shuttle run) were measured. SA was assessed with the TW2 RUS, TW3 RUS, and Fels methods; each SA was expressed as the standardized residual of the regression of SA on CA (SAsr). Hierarchical multiple regression was used. Results: Body size accounted for ≥50% of the variance in grip strength in both CA groups; the body size × SAsr for each method and SAsr alone added little to the explained variance. Body size, body size × SAsr interactions, and SAsr per se with each method accounted for small percentages of variance in motor tasks among players 9–12 years, while body size explained a larger proportion of variance in motor tasks (except the endurance run) among players 13–16 years; body size × SAsr interactions for TW2 and TW3 more so than Fels added to the explained variances. For the endurance run, only SAsr per se with each method accounted for significant portions of the variance. Conclusion: Body size and the three estimates of SA significantly influenced strength and motor performance, but the explained variance varied between CA groups and among SA methods and performance tasks. [ABSTRACT FROM AUTHOR]

Conventional energy sources like fossil fuels are no longer viable due to their limitations and environmental impact. The demand for cleaner, more efficient energy solutions has led to the development of electric machines with smaller volumes and higher output. The family of permanent magnet Vernier motors have high torque output at very low speeds while being very small in volume. In conventional SVPM, the core losses are high, which leads to heating and reducing the efficiency of the motor, and the power factor of the motor is also low, and the torque can increase in relation to the motor volume. The reluctance torque theory, along with the normal output torque of the motor, increases the final torque of the motor. In addition, the toothing of the rotor reduces the cross-sectional area and weight of the rotor. With the reduction of the cross-sectional area, the eddy currents in the core are reduced, the power factor increases and the efficiency of the motor improves. Therefore, in this paper, a spoke-type permanent magnet Vernier motor with a rotor similar to the reluctance rotor has been designed, which has higher torque, lower losses, and higher power factor compared to conventional spoke-type permanent magnet Vernier motors. [ABSTRACT FROM AUTHOR]

Patients with motor impairments (e.g., stroke, bone fracture, Parkinson's) are sensitive to the wearing experience of rehabilitation devices, and they often have difficulty accurately positioning them at an accurate position. While solutions involving optical systems or IMUs could potentially help alleviate the issue, they often introduce other challenges such as privacy concerns or discomforting experiences. With the emergence of wearable soft sensors during the last few decades, researchers widely apply soft sensors in rehabilitation to improve the wearing experience. However, these approaches have primarily focused on analyzing the sensor readings to improve accuracy rather than addressing the needs of patients and healthcare providers, and there is a lack of comprehensive design investigation and need assessment based on soft sensor-based rehabilitation systems for motor-impaired patients and their doctors. In this study, we developed an application, RehabFAB, utilizing fabric sensors for rehabilitation purposes. Besides, we evaluated our application and device and investigated the needs of patients and doctors for potential home rehabilitation applications. The investigation was conducted through thematic analysis, correlation analysis and System Usability Scale. The experimental results validated the efficacy, reliability and usability of our approach, with a SUS score of 81.75. In addition, the RehabFAB meets the expectations of motor-impaired patients and medical professionals as a home rehabilitation tool. Our core contributions lie in a thorough evaluation of the needs of motor-impaired patients in order to design a stable and reliable motion-tracking device based on soft sensors for their recovery. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) generally progresses slowly, but it is controversial whether delaying treatment accelerates the progression. Objective: Determine the correlation between the time of dopaminergic replacement treatment initiation and the severity of clinical symptoms in PD, including motor and non-motor symptoms. Methods: PD patients were divided between 155 people who were diagnosed de novo and 165 PDpatients receiving dopamine replacement therapy. Basic patient characteristics included gender, age, age at onset, disease duration, and the time of dopaminergic replacement treatment initiation. We used MDS-UPDRS scores to evaluate the severity of motor symptoms and we also used the scale to assess the severity of non-motor symptoms such as cognition, mood, sleep, and quality of life. Results: The mean time between symptom onset and the initiation of drug treatment was 31.0 (22.5) months. After adjusting for age, sex, age at onset, and disease duration, we found that the MDS-Unified Parkinson's Disease Rating Scale (UPDRS)-III score increased faster in the de novo group with a similar disease duration (F = 8.7, p = 0.0034) than the treatment group. The cumulative incidence of progression to H-Y score 3 in de novo PD group over disease duration was 39.7% in 50months and 92.2% in 100 months, while in treated group such cumulative incidence was 15.5% in 50 months, 51.4% in 100 months and 81.5% in 150 months. The cumulative incidence of patients in the de novo PD group was higher than that in the treated group (p = 0.001), suggesting that untreated patients were more likely to progress to the advanced stages. Symptoms onset, the time between symptomonset and treatment initiation, age, sex, and disease duration explained 28.95% of the total variation in the MDS-UPDRS-III score for motor symptoms. In drug-naïve patients, the time between symptom onset and treatment initiation explained 20.1% of the total variation in the MDS-UPDRS-III score for motor symptoms (t = 6.15, p < 0.001). Conclusions: These data in our study showed that early dopaminergic replacement treatment have played a positive role in PD patients, while dopaminergic replacement delayed treatment might be detrimental to motor symptoms and non-motor state of PD patient. Recognizing early stage symptoms of PD and early diagnosis are of great significance to treatment. [ABSTRACT FROM AUTHOR]

Background: Assessments of arm motor function are usually based on clinical examinations or self-reported rating scales. Wrist-worn accelerometers can be a good complement to measure movement patterns after stroke. Currently there is limited knowledge of how accelerometry correlate to clinically used scales. The purpose of this study was therefore to evaluate the relationship between intermittent measurements of wrist-worn accelerometers and the patient's progression of arm motor function assessed by routine clinical outcome measures during a rehabilitation period. Methods: Patients enrolled in in-hospital rehabilitation following a stroke were invited. Included patients were asked to wear wrist accelerometers for 24 h at the start (T1) and end (T2) of their rehabilitation period. On both occasions arm motor function was assessed by the modified Motor Assessment Scale (M_MAS) and the Motor Activity Log (MAL). The recorded accelerometry was compared to M_MAS and MAL. Results: 20 patients were included, of which 18 completed all measurements and were therefore included in the final analysis. The resulting Spearman's rank correlation coefficient showed a strong positive correlation between measured wrist acceleration in the affected arm and M-MAS and MAL values at T1, 0.94 (p < 0.05) for M_MAS and 0.74 (p < 0.05) for the MAL values, and a slightly weaker positive correlation at T2, 0.57 (p < 0.05) for M_MAS and 0.46 − 0.45 (p = 0.06) for the MAL values. However, no correlation was seen for the difference between the two sessions. Conclusions: The results confirm that the wrist acceleration can differentiate between the affected and non-affected arm, and that there is a positive correlation between accelerometry and clinical measures. Many of the patients did not change their M-MAS or MAL scores during the rehabilitation period, which may explain why no correlation was seen for the difference between measurements during the rehabilitation period. Further studies should include continuous accelerometry throughout the rehabilitation period to reduce the impact of day-to-day variability. [ABSTRACT FROM AUTHOR]

Motors are widely employed in mechatronic systems, especially in precision multiple degrees of freedom motion systems. In most applications, the dynamic equation between the motor instruction and the actual driving force is simplified as a constant. Subsequently, the static decoupling method can be utilized to design the feedback controller. However, in high-precision mechatronic systems, motor dynamics cannot be neglected, and the static decoupling performance is compromised due to discrepancies between motors. In this paper, a dynamic decoupling method is developed to improve the decoupling performance of the multiple-input multiple-output systems. The effects of transmission delays, motor dynamics, and discrepancies between different motors are taken into consideration in the dynamic decoupling method. Furthermore, a data-driven optimization method is developed to estimate the parameters of the dynamic decoupling controller. The effectiveness and superiority of the proposed method are demonstrated through numerical simulations. The experimental results show that the dynamic decoupling control method can achieve a 97.75 % performance improvement at least compared to the static decoupling control method. [ABSTRACT FROM AUTHOR]

Electric machines emulators (EMEs) based on hardware-in-the-loop (HIL), which effectively act as emulators to mimic the actual motor behavior of Interior Permanent Magnet (IPM) machines. EME is frequently used to evaluate motor controller and motor control methodologies prior to development. The inverse magnetization motor model, which is used as the basis for real-time simulation in this paper's proposal for an electric machine emulator system based on HIL, uses FEA to create the motor model data. The nonlinear features of the motor may be successfully replicated with this motor model, and the accuracy of the electric machine emulator can be enhanced by using a straightforward and trustworthy motor controller. The real-time simulation tool typhoon HIL is used in the study to develop a hardware-in-the-loop simulation platform for an IPM electric machines emulator. [ABSTRACT FROM AUTHOR]

Due to its central role in cell biology, the cytoskeleton is a key regulator of viral infection, influencing nearly every step of the viral life cycle. In this review, we will discuss the role of two key components of the cytoskeleton, namely the actin and microtubule networks in early HIV‐1 infection. We will discuss key contributions to processes ranging from the attachment and entry of viral particles at the cell surface to their arrival and import into the nucleus and identify areas where further research into this complex relationship may yield new insights into HIV‐1 pathogenesis. [ABSTRACT FROM AUTHOR]

Fine motor skills are heritable and comprise important milestones in development, and some evidence suggests that impairments in fine motor skills are associated with neurodevelopmental conditions, psychiatric disorders, and poor educational outcomes. In a preregistered study of 9625 preschool children from TEDS (Twins Early Development Study), fine motor assessments (drawing, block building, folding, and questionnaires) were conducted at 2, 3, and 4 years of age. A cross-age fine motor score was derived using principal component analysis. Multivariate regression analysis was used to examine the relationships between the fine motor score and neurodevelopmental traits, psychopathology, and educational outcomes at 3 later ages (7–8, 12, and 16 years) and cross-age psychopathology composite scores. Polygenic scores (PGSs) were created for attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, anxiety, major depressive disorder, obsessive-compulsive disorder, and years of education. We ran single-PGS models and a multi-PGS model. Fine motor skills were negatively associated with neurodevelopmental traits and psychopathology across childhood and adolescence and positively associated with educational achievement in adolescence (β = 0.25, p <.001). Superior fine motor skills were associated with a higher years-of-education PGS (β = 0.07, p <.001), a lower ADHD PGS (β = −0.04, p =.011), and a higher anxiety PGS (β = 0.03, p =.040). Similarly, the multi-PGS model retained the PGSs for years of education (β = 0.07), ADHD (β = −0.03), and anxiety (β = 0.01). A non-preregistered analysis in an independent preschool sample replicated the ADHD PGS association, but not the years of education or anxiety PGS associations. Fine motor skills are linked genetically and phenotypically to later neurodevelopment, psychopathology, and educational outcomes. Future work should investigate the mechanisms that underlie the role of fine motor development in later outcomes. [ABSTRACT FROM AUTHOR]

Background: Neurodegenerative diseases, such as Parkinson's disease (PD), necessitate frequent clinical visits and monitoring to identify changes in motor symptoms and provide appropriate care. By applying machine learning techniques to video data, automated video analysis has emerged as a promising approach to track and analyze motor symptoms, which could facilitate more timely intervention. However, existing solutions often rely on specialized equipment and recording procedures, which limits their usability in unstructured settings like the home. In this study, we developed a method to detect PD symptoms from unstructured videos of clinical assessments, without the need for specialized equipment or recording procedures. Methods: Twenty-eight individuals with Parkinson's disease completed a video-recorded motor examination that included the finger-to-nose and hand pronation-supination tasks. Clinical staff provided ground truth scores for the level of Parkinsonian symptoms present. For each video, we used a pre-existing model called PIXIE to measure the location of several joints on the person's body and quantify how they were moving. Features derived from the joint angles and trajectories, designed to be robust to recording angle, were then used to train two types of machine-learning classifiers (random forests and support vector machines) to detect the presence of PD symptoms. Results: The support vector machine trained on the finger-to-nose task had an F1 score of 0.93 while the random forest trained on the same task yielded an F1 score of 0.85. The support vector machine and random forest trained on the hand pronation-supination task had F1 scores of 0.20 and 0.33, respectively. Conclusion: These results demonstrate the feasibility of developing video analysis tools to track motor symptoms across variable perspectives. These tools do not work equally well for all tasks, however. This technology has the potential to overcome barriers to access for many individuals with degenerative neurological diseases like PD, providing them with a more convenient and timely method to monitor symptom progression, without requiring a structured video recording procedure. Ultimately, more frequent and objective home assessments of motor function could enable more precise telehealth optimization of interventions to improve clinical outcomes inside and outside of the clinic. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for detecting and classifying faults in dynamic control systems empowered with DC motors, operating under laboratory conditions. The approach employs a convolutional neural network model enhanced with an artificial endocrine influence to evaluate the condition of the rotating motor shaft by analysing information from the vibration sensors mounted on the shaft itself. The trained network effectively classifies the level of unbalance in the system into three categories based on the vibrations: optimal (no unbalance), first and second degree of unbalance. To validate the efficiency of the proposed model, its performance was compared with the performance of deep learning algorithms commonly recommended for time-series classification: default convolutional neural network, fully convolutional neural network, and residual network. The new model was shown to perform classification tasks with the highest accuracy, proving to be an efficient fault diagnosis tool with a viable potential to be applicable in industrial predictive maintenance processes. [ABSTRACT FROM AUTHOR]

The demand for high-power density motors has been increasing due to their remarkable output capability and compact construction. To achieve a significant improvement in motor power density, lightweight design methods have been recognized as an effective enabler. Therefore, extensive investigations have been conducted to reduce motor mass and achieve lightweight configurations through the exploration of lightweight materials, structures and manufacturing techniques. This article provides a comprehensive review and summary of state-of-the-art lightweight implementation methods for electrical machines, including the utilization of lightweight materials, structural lightweight design, and incorporation of advanced manufacturing technologies, such as additive manufacturing techniques. The advantages and limitations of each approach are also discussed in this paper. Furthermore, some comments and forecasts on potential future methodologies for motor lightweighting are also provided. [ABSTRACT FROM AUTHOR]

Reduced complexity during the writhing period can be crucial in the spontaneous movements of high-risk infants for neurologic impairment. This study aimed to verify the association between quantified complexity of upper and lower-limb movements at term-equivalent age and motor development in very-preterm or very-low-birth-weight infants. Video images of spontaneous movements at term-equivalent age were collected from very-preterm or very-low-birth-weight infants. A pretrained pose-estimation model and sample entropy (SE) quantified the complexity of the upper- and lower-limb movements. Motor development was evaluated at 9 months of corrected age using Bayley Scales of Infant and Toddler Development, Third Edition. The SE measures were compared between infants with and without motor developmental delay (MDD). Among 90 infants, 11 exhibited MDD. SE measures at most of the upper and lower limbs were significantly reduced in infants with MDD compared to those without MDD (p < 0.05). Composite scores in the motor domain showed significant positive correlations with SE measures at most upper and lower limbs (p < 0.05). The results show that limb-movement complexity at term-equivalent age is reduced in infants with MDD at 9 months of corrected age. SE of limb movements can be a potentially useful kinematic parameter to detect high-risk infants for MDD. [ABSTRACT FROM AUTHOR]

Response inhibition deficits in schizophrenia (SZ) are accompanied by reduced neural activities using event‐related potential (ERP) measurements. However, it remains unclear whether the reduction in inhibition‐related ERPs in SZ is contingent upon prepotent motor tendencies. This study aimed to examine the relationship between ERP markers of prepotent motor activity (lateralised readiness potential, LRP) and response inhibition (P3) by collecting behavioural and EEG data from healthy control (HC) subjects and SZ patients during a modified Go/No‐Go task. A trial‐averaged analysis revealed that SZ patients made more commission errors in No‐Go trials compared with HC subjects, although there was no significant difference in the inhibition‐related P3 effect (i.e. larger P3 amplitudes in No‐Go compared with Go trials) between the two groups. Subsequently, No‐Go trials were sorted and median‐split into bins of stronger and weaker motor tendencies. Both HC and SZ participants made more commission errors when faced with stronger motor tendencies. The LRP‐sorted P3 data indicated that HC subjects exhibited larger P3 effects in response to stronger motor tendencies, whereas this trial‐by‐trial association between P3 and motor tendencies was absent in SZ patients. Furthermore, SZ patients displayed diminished P3 effects in No‐Go trials with stronger motor tendencies but not in trials with weaker motor tendencies, relative to HC subjects. Taken together, these findings suggest that SZ patients are unable to dynamically adjust inhibition‐related neural activities in response to changing inhibitory control demands and emphasise the importance of considering prepotent motor activity when investigating the neural mechanisms underlying response inhibition deficits in SZ. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) is a rare yet debilitating neurodegenerative disorder originating from an increase in CAG repeats within the HTT gene. Despite ongoing research, a curative treatment for HD remains elusive, with current therapeutic strategies primarily targeting symptom management. Among the spectrum of HD symptoms, motor impairments are often the most obvious and disabling. To standardize treatment regimens and enhance patient care and quality of life, global evidence-based Clinical Practice Guidelines (CPGs) have been published to reduce variations in care. The integration of these guidelines into clinical information systems could significantly improve physician adherence to them, thereby optimizing patient outcomes. This study aims to develop an openEHR template specifically designed to represent recommendations for managing Huntington's motor symptoms, contributing to standardized care delivery, and enabling the seamless exchange of treatment information among different healthcare providers involved in the management of HD. We assessed the International Guidelines for the Treatment of Huntington's Disease commissioned by the European Huntington's Disease Network (EHDN) and selected the most representative variables regarding the HD motor symptoms. The openEHR template development followed the methodological guidance of the openEHR data modeling approach ('odma'). A total of 101 data items were extracted from the guideline section related to motor symptoms. After the classification and merging of these data elements, six domain concepts were organized for the motor symptom's treatment of Huntington's disease. This study successfully developed an openEHR template for managing Huntington's disease motor symptoms. These advancements have the potential to enhance treatment outcomes and transform care delivery for Huntington's disease. [ABSTRACT FROM AUTHOR]

This research aimed to identify relations of cognitive and power capacities with reactive agility in pubescent boys (n = 55) and girls (n = 46). Cognitive abilities were evaluated by the Stroop test, while the BlazePod system was used to evaluate agility performance conducting 20 yard shuttle and triangle tests of non-reactive (TCODS) and reactive agility (TRAG), respectively. Performance in jumping power was assessed through the squat jump (SJ), countermovement jump (CMJ), and drop jump (DHJ) utilising the Opto Jump system (Microgate, Bolzano, Italy), while sprinting ability over distances of 10 and 20 m was measured using a photocells system. A principal component was extracted from the four Stroop test variables using factor analysis. Forward stepwise multiple regression analysis was conducted separately for boys and girls to evaluate the multivariate relationships among the predictors and the criterion. Among boys, 80% of the TRAG variance was explained (MultipleR = 0.9), with TCODS and SJ as significant predictors (β = 0.53 and −1.01, respectively). For girls, the TCODS was the significant predictor (β = 0.65), explaining 43% of the variance (MultipleR = 0.65). These results show that (i) cognitive abilities measured with the Stroop test were not a reliable tool for predicting TRAG, (ii) jumping power was a significant predictor of TRAG in boys, and (iii) TCODS was a significant predictor of TRAG in girls. The findings indicated that cognitive abilities do not significantly influence reactive agility in pubescent children. It seems that power features have a greater influence on reactive agility, particularly in boys who have more developed motor skills at this age compared to girls. [ABSTRACT FROM AUTHOR]

High speed motors are widely used in industrial applications owing to their unique features, such as compact framework, high performance, and high reliability. Based on the finite volume method and numerical heat transfer theory, this study establishes a stator-air gap-rotor model, and the flow and heat transfer in the air gap between the stator and rotor in a high speed motor are investigated with high pressure natural gas as the cooling medium. Meanwhile, the "radial tri-vortex partition, alternating axial distribution" feature of the turbulent Taylor-Couette vortex in the air gap of the motor is determined. Then, the optimal structural parameters which can realize the heat transfer enhancement of motor air gap are obtained. Finally, an optical fiber grating temperature measurement system based on the wavelength division multiplexing technology is utilized to attain the temperature distributions on the stator and rotor surfaces. The simulation results are compared with the experimental data to evaluate the simulation method's precision. [ABSTRACT FROM AUTHOR]

The assessment of fine motor competence plays a pivotal role in neuropsychological examinations for the identification of developmental deficits. Several tests have been proposed for the characterization of fine motor competence, with evaluation metrics primarily based on qualitative observation, limiting quantitative assessment to measures such as test durations. The Placing Bricks (PB) test evaluates fine motor competence across the lifespan, relying on the measurement of time to completion. The present study aims at instrumenting the PB test using wearable inertial sensors to complement PB standard assessment with reliable and objective process-oriented measures of performance. Fifty-four primary school children (27 6-year-olds and 27 7-year-olds) performed the PB according to standard protocol with their dominant and non-dominant hands, while wearing two tri-axial inertial sensors, one per wrist. An ad hoc algorithm based on the analysis of forearm angular velocity data was developed to automatically identify task events, and to quantify phases and their variability. The algorithm performance was tested against video recordings in data from five children. Cycle and Placing durations showed a strong agreement between IMU- and Video-derived measurements, with a mean difference <0.1 s, 95% confidence intervals <50% median phase duration, and very high positive correlation (ρ > 0.9). Analyzing the whole population, significant differences were found for age, as follows: six-year-olds exhibited longer cycle durations and higher variability, indicating a stage of development and potential differences in hand dominance; seven-year-olds demonstrated quicker and less variable performance, aligning with the expected maturation and the refined motor control associated with dominant hand training during the first year of school. The proposed sensor-based approach allowed the quantitative assessment of fine motor competence in children, providing a portable and rapid tool for monitoring developmental progress. [ABSTRACT FROM AUTHOR]

Environmental characteristics of kindergartens are important for the development of kindergarten-aged children. However, knowledge of the role of kindergarten play environments in developing children's fundamental movement skills is limited. A pilot study was carried out to compare the fundamental movement skills of 3.5- to 5-year-old children in two kindergarten groups. One group had access to a traditional playground, an indoor room for active play, and had weekly trips. The other group had access to a nature-based playground. Fundamental movement skills were measured using the short form of the Bruininks-Oseretsky Test of Motor Proficiency, second edition test. In total, 28 children participated—11 children attended the kindergarten group with the traditional playground, and 17 children attended the kindergarten group with the nature-based playground. The total test score was 14.64 for children with access to a traditional playground and 16.71 for children with access to a nature-based playground. However, no statistically significant difference between the groups in total test score and the individual tests was found. It might be that space and diversity of features are more important than exposure to nature. In future research, more robust longitudinal studies with larger samples are required to investigate different kindergarten playground designs and environmental features related to motor skill development. [ABSTRACT FROM AUTHOR]

An external focus of attention and autonomy support are identified as key factors to optimize motor learning; however, research in children is limited. Moreover, research has failed to examine these factors in ecologically valid motor learning settings, like physical education. Therefore, the present study examined the effects of external focus of attention when delivered using autonomy-supportive or controlling instructional language on children's motor learning. Thirty-three novice participants (10.30 ± 0.52 years) practiced a land-based curling task under supportive (external-focus instructions delivered with supportive language), controlling (external-focus instructions delivered with controlling language), or neutral (external instructions embedded in the task aim) conditions before completing a retention and transfer test. The supportive group produced higher positive affect after practice and greater accuracy in the retention test compared with the other groups. The findings provide support for the OPTIMAL (optimizing performance through intrinsic motivation and attention for learning) theory of motor learning that combining an external focus and autonomy support conditions improves motor learning. [ABSTRACT FROM AUTHOR]

Introduction/purpose: Despite the era of digitization, the assessment of the combat readiness of modern army members has always been associated with good physical fitness. When it comes to the specific physical abilities of the Military Academy cadets, their previous tests indicate that the values are within the expected limits. The aim of this work is to compare the values of the results in the specific motor skills of cadets by classes (groups) after the second year of schooling. It is hypothesized that there are differences in the results of the cadets by groups. Methods: The sample consisted of a total of 932 male cadets within nine groups, after the second year of study, starting from the 2012/2013 school year. Four variables related to specific motor skills were included: pull-ups on a bar for 2 minutes, crunches for 2 minutes, 3200 m running, and overcoming infantry obstacles. Using statistical programs, the results of these four variables were processed through central and dispersion parameters. The univariate analysis of variance (ANOVA) was used to determine the differences between the groups in the achieved results. The multivariate analysis of variance (MANOVA) determined the differences in the system of variables with spaces. Results: The analysis of the results of the specific motor abilities by groups after the second year of study determined that there are statistically significant differences in the variables “pull-ups on a bar” and “crunches”, while there are no statistically significant differences in the variables “3200 m running” and “overcoming infantry obstacles”. Conclusions: The values of the results of the cadets in these four specific motor abilities are obviously within the limits provided by the Instructions and standards for evaluating cadets by age, so it was determined that there are no greater deviations than expected. [ABSTRACT FROM AUTHOR]

In the signal analysis context, the entropy concept can characterize signal properties for detecting anomalies or non-representative behaviors in fiscal systems. In motor fault detection theory, entropy can measure disorder or uncertainty, aiding in detecting and classifying faults or abnormal operation conditions. This is especially relevant in industrial processes, where early motor fault detection can prevent progressive damage, operational interruptions, or potentially dangerous situations. The study of motor fault detection based on entropy theory holds significant academic relevance too, effectively bridging theoretical frameworks with industrial exigencies. As industrial sectors progress, applying entropy-based methodologies becomes indispensable for ensuring machinery integrity based on control and monitoring systems. This academic endeavor enhances the understanding of signal processing methodologies and accelerates progress in artificial intelligence and other modern knowledge areas. A wide variety of entropy-based methods have been employed for motor fault detection. This process involves assessing the complexity of measured signals from electrical motors, such as vibrations or stator currents, to form feature vectors. These vectors are then fed into artificial-intelligence-based classifiers to distinguish between healthy and faulty motor signals. This paper discusses some recent references to entropy methods and a summary of the most relevant results reported for fault detection over the last 10 years. [ABSTRACT FROM AUTHOR]

The bearingless motor with dual-winding embedded in the stator can not only produce electromagnetic torque and can also produce suspension force to support the rotor suspension, and the design of the dual-winding will directly affect the torque and suspension performance of the motor. It is a complex problem of multi-objective optimization, multi-performance coupling, and multi-parameter collaborative optimization, which is great significance to improve the comprehensive performance of the motor. Firstly, in order to solve the problem of slot space ratio and turns design of dual-winding under the restriction of stator slot space and thermal loading, the calculation formulas of the electromagnetic torque and the suspension force are derived. The influence of dual-winding design on electromagnetic loading, thermal loading, torque and suspension performance are analyzed. The linear variation of electromagnetic torque with the slot space ratio of torque winding is obtained, and the influence of the dual-winding magnetic motive force on suspension force is clarified. Secondly, in order to obtain the dual-winding design scheme with the optimal torque and suspension performance, the performance parameters of the motor are calculated by finite element method and the influence of the slot space ratios of the torque winding on the torque and suspension performance is analyzed. Based on the coupling analysis of the electromagnetic torque and the suspension force in the case of different thermal loading distributions of dual-winding, the dual-winding optimal design of the bearingless motors is given. Finally, the suspension force of a prototype is tested by experiment. [ABSTRACT FROM AUTHOR]

Introduction: We aimed to evaluate the relationship between the hand fine motor skills of peritoneal dialysis (PD) practitioners and PD‐related peritonitis. Methods: This multicenter prospective observational study was conducted with 120 incident PD patients. Patients were divided into two groups who had PD‐related peritonitis within the first year as Group 1, and those who did not as Group 2. Hand fine motor skills were evaluated by Nine‐Hole Peg Test (NHPT) and Nut Screwing Test (NST). Results: Initial NHPT (28.5 ± 6.0 s vs. 25.8 ± 5.0 s, p = 0.011) and NST (82.3 (61.5–102.8) s versus 65.3 (52.3–88.5) s p = 0.023) scores were significantly higher in Group 1 than Group 2. In multivariate logistic regression analysis, NHPT, Body Mass Index, Mini‐Mental Test, self PD practitioner, and catheter complications were found to be independent variables in predicting PD‐related peritonitis. Conclusion: Decreased hand fine motor skills of PD patients is a risk factor for peritonitis. [ABSTRACT FROM AUTHOR]

Electrification is increasing in prevalence due to the importance placed on it for achieving global net zero targets. This has led to the proliferation of electrical mobility, including the wide-scale production of passenger vehicles, personal mobility devices and recent announcements regarding electrically powered aircraft, as well as in energy production. Electrical machines provide a cleaner source of energy during operation in comparison to their traditional fossil-based alternatives. The uncertainty and lack of transparency hanging over these green credentials can be attributed to how these products are manufactured and then disposed of at the end of their life. For them to be a truly sustainable solution, improvements need to be made across their entire life cycle. With the projected increase in their numbers due to the advancement of electrification, this current life cycle is not sustainable, directly opposing the intention of these products. This paper will introduce the current demand and challenges. It will also present these motors broken down into their constituent parts and follow each through their typical lifecycle. This paper presents the typical current life cycle of permanent magnet electrical machines, demonstrating the environmental issues associated with the current linear life cycle, and proposing alternative practices, to ease the environmental burden. [ABSTRACT FROM AUTHOR]

This article explains the mechanics, control strategies and main applications of a new concept which achieves a balance between energy saving and driver comfort. A physical and mathematical model of a suspension system with energy recovery is presented. It shows practical implementation of the BLDC braking system with energy recovery in a horizontal seat suspension and a detailed simulation analysis of their features and performance. The research involves a specific solution, with a specific BLDC motor, and experimental tests on a laboratory stand. The results of the simulation study using a simplified biomechanical model and experimental studies with human participation are presented. [ABSTRACT FROM AUTHOR]

In this work, we present an experiment that illustrates an electromechanical energy conversion between a DC motor and electrolytic capacitors. The DC motor is coupled to a rigid disk and initially powered by a voltage supply, then the power supply is disconnected, and the electrical machine is connected to an electric diode in series with a capacitor bank. The stored charge in the capacitor bank demonstrates that the device, previously working as a DC motor, starts operating as an electric generator. The proposed experiment can be used to discuss the physical model of DC motor, induced electromotive forces, diode characteristic curve, and dynamics of the capacitors. We present a comprehensive mathematical model for the capacitor charging dynamics and characterize the relevant circuit parameters. Computational simulations are performed and predicted final capacitor voltages and electromechanical conversion efficiencies are compared with the experimental data. The overall agreement between the proposed model and experimental data is very good.

Preventive maintenance of rotating machinery, such as motors, is pivotal for cost reduction in manufacturing facilities. Condition-based maintenance is considered the driving force in the health management of industrial machinery, which necessitates the development of efficient, able-to-generalize, and reusable approaches to help manufacturing facilities identify operational conditions. This study proposes an approach for classifying the operational settings of motors based on vibration data. This was accomplished by first creating a merged class of weight distribution and speed percentage ranges to be classified. These two operational settings can be classified to address sustainable manufacturing concerns as they relate to the development of systematic maintenance plans. Ensemble learning was then used as the machine learning algorithm of choice for the classification task. It was found that ensemble learning is capable of producing reasonable classification accuracy results that are superior to those of single-model approaches. In addition, the testing size and window size of the segmented vibration signals have been identified to have a clear effect on classification accuracy that is considered consistent with the logical trend. The proposed approach addresses the need for manufacturing facilities to utilize efficient and accurate algorithms for cost-effective, and sustainable maintenance practices.