Electrophysiological Biomarkers for the Assessment of Motor Efficiency in Sport

Many disciplines have approached the study of human motor behavior. The motor learning theory based on information processing proposes a learning loop through interaction between the external environment and the central nervous system. Different neuroscience fields and technological advances provide a new perspective for the intensive study of the intrinsic processes of motor behavior, which modify the most visible aspect: motor efficiency. The aim of the present review was to determine which cortical and muscular electrophysiological biomarkers available in the literature could be representative for the study and quantification of motor efficiency. In this review, a survey of the literature related to motor production has been performed. The continuous development of biological signal monitoring techniques has allowed to understand part of the communication methods of the central nervous system, the integration of neural networks, and the interaction between different anatomic structures through rhythmic patterns of discharge known as brain waves. Motor production has been characterized by detecting electrophysiological biomarkers, taking into account the connectivity that can be represented by the corticomuscular and intermuscular coherence indices in different frequency bands. The present work proposes an approach to use these biomarkers on beta-band (for muscle stability synergies) and gamma-band (for mobility synergies). These indices will allow establishing quantitative parameters for motor efficiency, which could improve the precision of sports assessment.

Power Consumption Simulation of Servo Motors Focusing on the Influence of Mechanical Vibration on Motor Efficiency

This paper presents a simulation method for the power consumption of servo motors, focusing on the influence of vibrations on the motor efficiency. An apparatus consisting of two servo motors connected through a coupling was specifically designed for this study. The efficiency of the servo motor was experimentally investigated for several torque vibration levels imposed through the selection of the control parameters, and the torque vibration level was quantified through the standard deviation of the torque signal. The efficiency map characteristics for each torque oscillating level were determined. A numerical model of the apparatus clarifying the dependency of the coupling characteristics on the oscillating torque was developed, and the torque oscillation of the system was simulated. A model based on the measured motor efficiency maps and the torque oscillation level was developed to simulate the motor efficiency under several torque vibrating conditions. Finally, the power consumption of the motor was simulated based on the simulated efficiency and mechanical power. A balance of input, output, and loss powers was presented, and the experimental measurements were compared with the simulation results. The power consumption of the motor increased when the torque oscillated owing to vibrations, and the loss of power due to both oscillations and the loss of motor efficiency was quantified.

Identifying the efficiency decrease factor of motors working under power harmornic in 660V electric mining grids

Purpose. Identify the motors efficiency decrease factor corresponding to various values of load-carrying ratio. Methods. Basing on the onsite measurements of power harmonic in 660V low voltage (LV) grids in Vietnam underground mines, simulations have been done on MATLAB and compared with mathematical models. Verifying data will be implemented in Lab-measurements carried out on pumping system to reveal series of decreasing factors. Findings. Series factors present the relation of the level of power total harmonic distortion (THD) and the decrease in motor efficiency with alternative load-carrying ratio. The factors will help mine operators to have better understanding of the power harmonics impact on 660V motors. Originality. The proposed factors and simulation in MATLAB may be applied to all underground mining grids with diffe-rent input parameters of THD. Practical implications. The research is implemented to identify the factors obtained from the operation of motors which work in high power harmonic environment. The resulting factors could be utilized to recalculate mining efficiency.

Impact of a Punching Process on the SyRM Iron Loss: SPICE Model as an Effective Tool for Iron Loss Modeling

Many technologies for cutting the magnetic laminations, from which electric motors cores are built, change material properties, among which are magnetizability and iron loss, thus affecting the motor parameters such as motor efficiency. This problem is particularly important for low-power motors, in which the dimensions of the magnetic circuit elements are relatively small. The correct estimation of the motor efficiency is important as early as at its design stage. This is possible when the correct material characteristics are used. This knowledge and analytical model enabling fast estimation of material properties (depending on the actual size) are necessary for engineers, who design electrical motors by analyzing many solution variants in a short time. The author proposes an analytical model of changing material properties, implemented in SPICE software. Its effectiveness was compared with measurement results while being a competitive solution in relation to other analytical models. The proposed SPICE model allowed evaluating material properties for lamination of any width. In the end, the knowledge concerning the material properties was used to calculate the iron loss in the stator of the SyRM motor, showing the need to use the material characteristics calculated for the specified width of the core piece.

Research on Optimal Torque Control of Turning Energy Consumption for EVs with Motorized Wheels

This paper aims to explore torque optimization control issue in the turning of EV (Electric Vehicles) with motorized wheels for reducing energy consumption in this process. A three-degree-of-freedom (3-DOF) vehicle dynamics model is used to analyze the total longitudinal force of the vehicle and explain the influence of torque vectoring distribution (TVD) on turning resistance. The Genetic Algorithm-Particle Swarm Optimization Hybrid Algorithm (GA-PSO) is used to optimize the torque distribution coefficient offline. Then, a torque optimization control strategy for obtaining minimum turning energy consumption online and a torque distribution coefficient (TDC) table in different cornering conditions are proposed, with the consideration of vehicle stability and possible maximum energy-saving contribution. Furthermore, given the operation points of the in-wheel motors, a more accurate TDC table is developed, which includes motor efficiency in the optimization process. Various simulation results showed that the proposed torque optimization control strategy can reduce the energy consumption in cornering by about 4% for constant motor efficiency ideally and 19% when considering the motor efficiency changes in reality.

PMSM Torque-Speed-Efficiency Map Evaluation from Parameter Estimation Based on the Stand Still Test

During the last decades, a wide variety of methods to estimate permanent magnet synchronous motor (PMSM) performance have been developed. These methodologies have several advantages over conventional procedures, saving time and economic costs. This paper presents a new methodology to estimate the PMSM torque-speed-efficiency map based on the blocked rotor test using a single-phase voltage source. The methodology identifies the stator flux linkage depending on the current magnitude and angle while providing a detailed estimation of the iron losses. The torque-speed-efficiency map provides detailed information of the motor efficiency along its operating region, including the nominal conditions and the maximum power envelope. The proposed methodology does not require knowing the geometry of the machine to perform any load test, and it also avoids using expensive measurement devices and a complex experimental setup. Moreover, the proposed method allows the PMSM performance to be reproduced by applying different control strategies, which is useful when testing different drives. The method does not require the application of any optimization algorithm, thus simplifying and speeding up the process to determine the performance. Experimental validation is carried out by comparing motor performances obtained through the proposed method with those obtained by means of a conventional experimental method and against finite element analysis (FEA).

A Novel Approach to Assessment of Perceptual-Motor Efficiency and Training-Induced Improvement in the Performance Capabilities of Elite Athletes

Standard clinical assessments of mild traumatic brain injury are inadequate to detect subtle abnormalities that can be revealed by sophisticated diagnostic technology. An association has been observed between sport-related concussion (SRC) and subsequent musculoskeletal injury, but the underlying neurophysiological mechanism is not currently understood. A cohort of 16 elite athletes (10 male, 6 female), which included nine individuals who reported a history of SRC (5 male, 4 female) that occurred between 4 months and 8 years earlier, volunteered to participate in a 12-session program for assessment and training of perceptual-motor efficiency. Performance metrics derived from single- and dual-task whole-body lateral and diagonal reactive movements to virtual reality targets in left and right directions were analyzed separately and combined in various ways to create composite representations of global function. Intra-individual variability across performance domains demonstrated very good SRC history classification accuracy for the earliest 3-session phase of the program (Reaction Time Dispersion AUC = 0.841; Deceleration Dispersion AUC = 0.810; Reaction Time Discrepancy AUC = 0.825, Deceleration Discrepancy AUC = 0.794). Good earliest phase discrimination was also found for Composite Asymmetry between left and right movement directions (AUC = 0.778) and Excursion Average distance beyond the minimal body displacement necessary for virtual target deactivation (AUC = 0.730). Sensitivity derived from Youden's Index for the 6 global factors ranged from 67 to 89% and an identical specificity value of 86% for all of them. Median values demonstrated substantial improvement from the first 3-session phase to the last 3-session phase for Composite Asymmetry and Excursion Average. The results suggest that a Composite Asymmetry value ≥ 0.15 and an Excursion Average value ≥ 7 m, provide reasonable qualitative approximations for clinical identification of suboptimal perceptual-motor performance. Despite acknowledged study limitations, the findings support a hypothesized relationship between whole-body reactive agility performance and functional connectivity among brain networks subserving sensory perception, cognitive decision-making, and motor execution. A complex systems approach appears to perform better than traditional data analysis methods for detection of subtle perceptual-motor impairment, which has the potential to advance both clinical management of SRC and training for performance enhancement.

Proposed Commutation Method for Performance Improvement of Brushless DC Motor

This study focused on the efficiency improvement and acoustic noise reduction of brushless DC (BLDC) motors by reducing current harmonics using a novel BLDC commutation method. To achieve these goals, we designed an improved 150° commutation method for a three-phase permanent magnet BLDC motor that can improve the current waveform. Although the 120° commutation method is generally employed for BLDC motors, an improved 150° commutation method is introduced to operate the BLDC with increased efficiency and acoustic noise similar to a brushless AC motor. This study investigated the attributes of various commutation methods, both theoretically and experimentally, to determine the optimal commutation method. The results of this study indicate that the improved 150° commutation method is optimal in terms of harmonic attributes and reduced torque ripple, allowing it to improve motor efficiency and reduce acoustic noise.

Children do not distinguish efficient from inefficient actions during observation

Observation is a powerful way to learn efficient actions from others. However, the role of observers’ motor skill in assessing efficiency of others is unknown. Preschoolers are notoriously poor at performing multi-step actions like grasping the handle of a tool. Preschoolers (N = 22) and adults (N = 22) watched video-recorded actors perform efficient and inefficient tool use. Eye tracking showed that preschoolers and adults looked equally long at the videos, but adults looked longer than children at how actors grasped the tool. Deep learning analyses of participants’ eye gaze distinguished efficient from inefficient grasps for adults, but not for children. Moreover, only adults showed differential action-related pupil dilation and neural activity (suppressed oscillation power in the mu frequency) while observing efficient vs. inefficient grasps. Thus, children observe multi-step actions without “seeing” whether the initial step is efficient. Findings suggest that observer’s own motor efficiency determines whether they can perceive action efficiency in others.