Search Results (13)

Integrating neural and muscular signals into wearable robotics enables adaptive assistance during real-world tasks. This study proposes a multimodal neural interface for passive exoskeletons that combines electroencephalography (EEG) and electromyography (EMG) signals to classify motor gestures and estimate real-time cognitive and muscular effort, supported by finite-element-based biomechanical modeling. The system was implemented on the Ottobock Shoulder X passive exoskeleton© and validated using synchronous EEG–EMG acquisition via the LiveAmp platform©, a commercially available platform that was not developed specifically for this study. A hybrid CNN–LSTM architecture with deep fusion was employed to enhance robustness and responsiveness under realistic operating conditions. This study proposes a multimodal neural interface for the software-level adaptive assistance of passive upper-limb exoskeletons. While the physical device maintains a static mechanical profile, the proposed digital framework achieves adaptation by interpreting the user’s physiological and motor states. Ten healthy participants performed three functional tasks (screwing, moving the box, and lifting the box) under five assistive conditions. Finite element modeling (FEM) was used to characterize the torque–angle relationship of the passive exoskeleton and to support the interpretation of experimentally observed assistive torque profiles. The FEM model, used as an offline biomechanical analysis tool to aid in the interpretation of experimental results, has not been integrated into the real-time control loop. Results showed an average classification accuracy of 90%, an F1-score of 0.85, and inference latency below 180 ms, confirming real-time applicability. Cognitive indices such as the Cognitive Load Index (CLI) and Frontal Asymmetry Index (FAI) enabled adaptive modulation of assistance strategies without requiring active actuation, thereby preserving the device’s intrinsic passive nature. Comparative torque analysis highlighted the ergonomic benefits of passive systems in mid-range postures, while Finite Element Method (FEM) supported analysis clarified their limitations under highly dynamic loads compared to active solutions. These findings advance multimodal brain–machine interfaces for wearable robotics by integrating physiological sensing, deep learning, and biomechanical modeling, offering a safe, energy-efficient, and adaptive approach with potential rehabilitation, occupational ergonomics, and human–robot applications. Full article

The effective allocation of Intensive Care Unit (ICU) beds is critical for balancing timely access across patient groups of differing clinical urgency, particularly during demand surges. This paper extends the threshold-based loss-queuing framework to three patient classes, emergency, semi-urgent, and elective, governed by a two-tier coordinate reservation policy with thresholds $(k_1,k_2)$. Under Poisson arrivals, we derive an exact product form steady-state distribution and closed-form blocking probabilities for all three classes; under Interrupted Poisson Process (IPP) arrivals, we construct a block-tridiagonal Markov chain over the full $(i,j,l,\xi )$ state space and obtain dimensionally consistent blocking formulas via a lifted rate matrix. Fitted to the publicly available MIMIC-IV Medical ICU dataset, the IPP captures bursty emergency arrival patterns with mean and variance deviations below $0.1\%$. A comprehensive parameter sensitivity sweep over traffic utilization $\rho \in [0.40,0.95]$ and burstiness index $z\in [1.0,5.0]$ identifies three distinct operating regimes and yields policy recommendation charts for direct clinical use. An adaptive optimization framework selects $(k_1^{*},k_2^{*})$ to minimize a weighted blocking loss subject to fairness constraints, achieving a Jain fairness index above $0.999$ throughout the high-load region. Analytical predictions are validated against discrete-event simulation with a $100\%$ pass rate at a ±1.5 percentage-point criterion. We further demonstrate that the blocking probabilities for all three classes are insensitive to the LoS distribution beyond its mean across six service-time distributions spanning coefficients of variation from $0.45$ to $2.24$, with a $100\%$ pass rate across all 72 (class, distribution, setting) combinations, broadening the model’s applicability to diverse real-world scenarios. The findings provide actionable guidance for ICU managers in determining fair and efficient three-tier bed reservation thresholds. Full article

This paper addresses active-mode detection for switched discrete-time Takagi–Sugeno systems from noisy input–output data under candidate-dependent input correction and uncertainty in data-driven observability subspaces. A lifted input–output formulation is developed in which each candidate mode is associated with a mode-dependent forced-response correction and a nominal observability subspace identified offline from representative data. Based on this construction, a practical residual criterion is introduced together with an ideal residual criterion defined by the exact residual projector. An online verifiable sufficient condition is then derived to guarantee consistency between the practical and ideal residual orderings, yielding a conservative but theorem-consistent certification mechanism. To quantify the effect of measurement uncertainty, a component-wise noise-to-signal ratio (NSR) analysis is established, leading to explicit conservative NSR bounds when signal-floor conditions are available offline. These results motivate an adaptive observation-window strategy driven by an explicit online NSR estimate. In addition, an uncertainty-corrected discernibility index based on principal angles between estimated observability subspaces is introduced to assess offline mode separability. Simulations on a switched T–S benchmark show high practical detection accuracy, sound but conservative certification, informative NSR bounds, and stable adaptive-window regulation, including under reviewer-motivated switching stress tests and baseline comparison experiments. Full article

This article assesses the potential for intra-day redistribution of the electrical load of water intake systems under different electricity tariff models, using water supply systems in Belarus and China as case studies. It demonstrates how tariff policy influences the electrical load profile of a water intake system and quantitatively evaluates the economic effect of optimizing the operating modes of pumping equipment. The analysis is based on daily profiles of electric power and water supply. For the Belarusian water supply system, data for 2019 were considered, corresponding to the baseline operating mode without targeted load management, and data for 2023 were considered after the transition to dispatch-based control of well activation with account taken of tariff constraints (without automation tools). For the Chinese water intake system, hourly data for 2025 were used. The load redistribution potential was assessed on the basis of lagged correlation between power and water supply profiles. In addition, the F-index was applied as an aggregated diagnostic indicator intended for the comparative assessment of potential load transferability across technological stages, taking into account their share in total energy consumption. For the Chinese case, it was shown that the maximum correlation between water supply and electricity consumption across all technological stages is achieved near zero lag, which indicates a high adaptation of system operating modes to current demand; at the same time, the R values were 0.19 for reservoir intake, 0.86 for water treatment, and 0.51 for the pumping station. In the Belarusian case, for the first-lift stage, the maximum correlation is shifted by −6 h relative to zero lag, indicating a less rigid linkage of pump operation to current demand and a more inertial response of the system. A comparison of 2019 and 2023 for the Belarusian facility showed that targeted regulation of well activation and load redistribution across tariff zones reduced the total electricity cost by 1.58%, confirming the potential for further optimization of electricity consumption regimes. Full article

In the harvesting operation, the stubble height of the grain is a vital parameter index in the combined harvesting operation; if the stubble is too high or too low, it will directly affect the harvesting quality and the service life of the header. At present, the profiling control system can only control the lift of the header in the vertical direction but not the horizontal direction and the angle of the cutter profiling. This study proposes a contouring control strategy and system for grain harvesting by analyzing the designed contouring adjustment mechanism and simulating the control method and hydraulic system through Amesim2404 software to simulate and analyze the control method and hydraulic system. Finally, different forward speeds of the harvester (5, 7, 9, and 11 km/h) and other cutting heights of the harvester were analyzed based on static and field tests and different stubble heights (100, 150, 200, and 250 mm) on the test indexes. The results of the field test showed that for different operating speeds, the error between the mean value of stubble height and the target value was small, the absolute error was less than 2 mm, the mean value of the coefficient of variation of stubble height was 4.53%, and the mean value of control accuracy is 94%. The developed adaptive control system of the profiled grain header has high precision and stability, which can provide a reference for the all-terrain profiling control technology of the combined harvester header deck. Full article

Material handling tasks often lead to skeletal injury of workers. The whole-body static biomechanical modeling method based on virtual humans is the theoretical basis for analyzing the human factor index in the lifting process. This paper focuses on the study of humans’ body static biomechanical model for virtual human ergonomics analysis: First, the whole-body static biomechanical model is constructed, which calculates the biomechanical data such as force and moment, average strength, and maximum hand load at human joints. Secondly, the prototype model test system is developed, and the real experiment environment is set up with the inertial motion capture system. Finally, the model reliability verification experiment and application simulation experiment are designed. The comparison results with the industrial ergonomic software show that the model is consistent with the output of the industrial ergonomic software, which proves the reliability of the model. The simulation results show that under the same load, the maximum joint load and the maximum hand load are strongly related to the working posture, and the working posture should be adjusted to adapt to the load. Upright or bent legs have less influence on the maximum load capacity of the hand. Lower hand load capacity is due to forearm extension, and the upper arm extension greatly reduces the load capacity of the hand. Compared with a one-handed load, the two-handed load has a greater load capacity. Full article

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed^®, Web of Science^®, Institute of Electrical and Electronics Engineers^®, Science Direct^® and Google Scholar^®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs. Full article

When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment. Full article

Once the high-speed railway tunnel is put into use, its resilience will determine the possibility of permanent safety of the tunnel due to the closure of the structural space of the high-speed railway tunnel in service. Resilience theory is introduced into a risk analysis of operating high-speed rail tunnels to improve the ability to respond to risks in operating high-speed rail tunnels and to relieve the aging phenomenon caused by changes in the tunnel with time. First, an evaluation framework for the safety resilience of existing high-speed railway tunnels is constructed. Starting from the attributes of resilience such as resistance, adaptability, and resilience, and considering the characteristics of high-speed railway tunnels, protective measures, emergency management measures, and other factors, we fit the risk factors and probability of accident type of the high-speed railway tunnel and establish a tunnel safety resilience evaluation index system with 10 indexes. Secondly, the method of information fusion is used to combine subjective weighting and objective weighting. Then, the comprehensive weight of the evaluation index is obtained based on the principle of minimum discriminant information. Thirdly, the system resilience evaluation model based on the TOPSIS improved fuzzy matter-element is constructed to determine the classification criteria of resilience. On this basis, based on the temporal and spatial variability of the ductile tunnel, the concepts of ductile transition and ductile attenuation are introduced and the tunnel toughness optimization model is established to suppress the attenuation situation, enhance the transition ability, and then improve the system resilience level. On this basis, an optimal lifting scheme is obtained. Finally, taking Ai-Min tunnel of Ha-Mu high-speed railway as the engineering background, the flexibility of the resilience system is calculated, and the resilience grade (3) of the rock system surrounding the tunnel is obtained. Combined with the numerical model, improvement measures for specific tunnel facilities are proposed. The results show that the Ai-Min tunnel system has a general ability to resist external intrusion and prevent disasters, and the resilience level is general. It should focus on improving the resilience level of the transition index. The resilience evaluation results of the evaluation model are consistent with the actual situation of the project. Full article

The purpose of this study was to compare the impact of velocity-based resistance training (VBRT) and percentage-based resistance training (PBRT) on anaerobic ability, sprint performance, and jumping ability. Eighteen female basketball players from a Sport College were randomly divided into two groups: VBRT (n = 10) and PBRT (n = 8). The six-week intervention consisted of two sessions per week of free-weight back squats with linear periodization from 65% to 95%1RM. In PBRT, the weights lifted were fixed based on 1RM percentage, while in VBRT, the weights were adjusted based on individualized velocity profiles. The T-30m sprint time, relative power of countermovement jump (RP-CMJ), and Wingate test were evaluated. The Wingate test assessed peak power (PP), mean power (MP), fatigue index (FI), maximal velocity (Vmax), and total work (TW). Results showed that VBRT produced a very likely improvement in RP-CMJ, Vmax, PP, and FI (Hedges’ g = 0.55, 0.93, 0.68, 0.53, respectively, p < 0.01). On the other hand, PBRT produced a very likely improvement in MP (Hedges’ g = 0.38) and TW (Hedges’ g = 0.45). Although VBRT showed likely favorable effects in RP-CMJ, PP, and Vmax compared to PBRT (p < 0.05 for interaction effect), PBRT produced greater improvements in MP and TW (p < 0.05 for interaction effect). In conclusion, PBRT may be more effective in maintaining high-power velocity endurance, while VBRT has a greater impact on explosive power adaptations. Full article

To ensure the quality of concrete construction, the workability of fresh mix measured by rational test methods is critical to be controlled. With the presence of steel fibers, whether the test methods and evaluation indices of fresh self-compacting concrete (SCC) are adaptable for self-compacting steel fiber reinforced concrete (SFRC) needs to be systematically verified. In this paper, seven groups of self-compacting SFRC, referenced with one group SCC, were prepared by using the mix proportion design method based on the steel fiber-aggregates skeleton packing test. The main factors included the volume fraction and the length of hooked-end steel fiber. Tests for filling ability, passing ability, and stability of fresh self-compacting SFRC and SCC were carried out. Results indicate that the adaptability was well for the slump-flow test with indices of slump flow and flow time T₅₀₀ to evaluate the filling ability, the J-ring flow test with an index of PA level to evaluate the passing ability, and the static segregation test with an index of static segregation resistance to evaluate the stability of fresh self-compacting SFRC. By the repeated tests and measurements, the slump cone should be vertically lifted off to a height of 300 mm within 3 s at a constant speed, the spacing of the rebar in the J-ring test should be adjusted to be two times the fiber length. If the table jumping test is used, the dynamic segregation percent should be increased to 35% to fit the result of the static segregation test. Good workability of the self-compacting SFRC prepared in this study is presented with the general evaluation of test results. Full article

Mild leg length discrepancy increases biomechanical asymmetry during gait, which leads to low-back pain. Orthotic insoles with a directly integrated heel lift were used to reduce this asymmetry and thus the associated low-back pain. The aim of this study was to analyze the biomechanical adaptations of the locomotor apparatus during gait and the subjective pain ratings before and after the establishment of orthotic insole use. Eight patients with mild leg length discrepancy (≤2.0 cm) underwent three-dimensional biomechanical analysis while walking before and after 3 weeks of orthotic insole use. Low-back pain was assessed separately before both measurement sessions using a visual analog scale. Analysis of the kinematic parameters highlighted individual adaptations. The symmetry index of Dingwell indicated that orthotic insoles had no significant effect on the kinematic gait parameters and an unpredictable effect across patients. Orthotic insole use significantly and systematically (in all of the patients) reduced low-back pain (P < .05), which was correlated with changes in ankle kinematics (P = .02, r = 0.80). The effects of orthotic insoles on gait symmetry are unpredictable and specific to each patient's individual manner of biomechanical compensation. The reduction in low-back pain seems to be associated with the improved ankle kinematics during gait. Full article

Due to the limitations of storage and transmission in remote sensing scenarios, lossy compression techniques have been commonly considered for remote sensing images. Inspired by the latest development in image coding techniques, we present in this paper a new compression framework, which combines the directional adaptive lifting partitioned block transform (DAL-PBT) with content-driven quadtree codec with optimized truncation (CQOT). First, the DAL-PBT model is designed; it calculates the optimal prediction directions of each image block and performs the weighted directional adaptive interpolation during the process of directional lifting. Secondly, the CQOT method is proposed, which provides different scanning orders among and within blocks based on image content, and encodes those blocks with a quadtree codec with optimized truncation. The two phases are closely related: the former is devoted to image representation for preserving more directional information of remote sensing images, and the latter leverages adaptive scanning on the transformed image blocks to further improve coding efficiency. The proposed method supports various progressive transmission modes. Experimental results show that the proposed method outperforms not only the mainstream compression methods, such as JPEG2000 and CCSDS, but also, in terms of some evaluation indexes, some state-of-the-art compression methods presented recently. Full article