Search Results (906)

Work-related musculoskeletal disorders (WMSDs) are a leading concern in industrial ergonomics, often stemming from sustained non-neutral postures and repetitive tasks. This paper presents a vision-based framework for real-time, frame-level ergonomic risk classification using a lightweight Vision Transformer (ViT). The proposed system operates directly on raw RGB images without requiring skeleton reconstruction, joint angle estimation, or image segmentation. A single ViT model simultaneously classifies eight anatomical regions, enabling efficient multi-label posture assessment. Training is supervised using a multimodal dataset acquired from synchronized RGB video and full-body inertial motion capture, with ergonomic risk labels derived from RULA scores computed on joint kinematics. The system is validated on realistic, simulated industrial tasks that include common challenges such as occlusion and posture variability. Experimental results show that the ViT model achieves state-of-the-art performance, with F1-scores exceeding 0.99 and AUC values above 0.996 across all regions. Compared to previous CNN-based system, the proposed model improves classification accuracy and generalizability while reducing complexity and enabling real-time inference on edge devices. These findings demonstrate the model’s potential for unobtrusive, scalable ergonomic risk monitoring in real-world manufacturing environments. Full article

Many commercial wearable sensor systems typically rely on a single continuous cardiorespiratory sensing modality, photoplethysmography (PPG), which suffers from inherent biases (i.e., differences in skin tone) and noise (e.g., motion and pressure artifacts). In this research, we present a wearable device that provides robust estimates of cardiorespiratory variables by combining three physiological signals from the upper arm: multiwavelength PPG, single-sided electrocardiography (SS-ECG), and bioimpedance plethysmography (BioZ), along with an inertial measurement unit (IMU) providing 3-axis accelerometry and gyroscope information. We evaluated the multimodal device on 16 subjects by its ability to estimate heart rate (HR) and breathing rate (BR) in the presence of various static and dynamic noise sources (e.g., skin tone and motion). We proposed a hierarchical approach that considers the subject’s skin tone and signal quality to select the optimal sensing modality for estimating HR and BR. Our results indicate that, when estimating HR, there is a trade-off between accuracy and robustness, with SS-ECG providing the highest accuracy (low mean absolute error; MAE) but low reliability (higher rates of sensor failure), and PPG/BioZ having lower accuracy but higher reliability. When estimating BR, we find that fusing estimates from multiple modalities via ensemble bagged tree regression outperforms single-modality estimates. These results indicate that multimodal approaches to cardiorespiratory monitoring can overcome the accuracy–robustness trade-off that occurs when using single-modality approaches. Full article

With the rapid technological advancements in wearable devices, motion and health management have significantly improved, enabling the measurement of various biometric data with compact equipment. Our research focuses on motion measurement but, in general, full-body motion estimation requires motion capture systems or multiple inertial sensors, making it necessary to directly measure movement itself. In this study, we propose estimating full-body posture using inverse kinematics based on trunk posture and limb-end information collected through wearable devices. To enhance estimation accuracy in this underdetermined problem, we employ Physics-Informed Neural Networks (PINNs), which efficiently learn using physical laws as a loss function, along with a high-precision inverse kinematics model of a digital human. Through this approach, we enable high-accuracy full-body posture estimation even with wearable devices in underdetermined scenarios. Full article

Background: Understanding the relationship between physical demands and game performance is essential to optimize player development and management in basketball. This study aimed to examine the association between game performance and physical demands in youth male basketball players. Methods: Fifteen players (16.3 ± 0.7 years) from a Spanish 4th division team were monitored over seven official games. Game performance variables were extracted from official statistics, including traditional and advanced metrics. Physical demands were monitored using an Electronic Performance Tracking System device, combining a positioning system and inertial sensors. Partial correlations, controlling for minutes played, were calculated to explore associations between physical demands and performance variables, both for the entire team and by playing position. Results: Significant correlations between physical demands and game performance were observed. Points scored correlated strongly with total distance and high-intensity accelerations, while assists correlated with high-intensity decelerations. Inertial metrics, such as player load and the number of jumps, showed large correlations with points, two-point attempts, and the efficiency rating. Positional analysis revealed stronger and more numerous correlations for centers compared to guards and forwards. Inertial sensor-derived metrics exhibited a greater number and strength of correlations than positioning metrics. Conclusions: Game performance and physical demands are intrinsically related, with specific patterns varying by playing position. Inertial sensors provide valuable complementary information to positioning systems for assessing physical demands in basketball. These findings can assist practitioners in tailoring monitoring and training strategies to optimize performance and manage player workload effectively. Full article

Based on experimental data regarding the local distribution of metallic impurities in raw selenium and the composition of its vapor phase, the potential composition of the vapor–droplet suspension that leads to reduced condensate quality due to impurities with low partial vapor pressures relative to selenium, as well as metals with vapor pressures comparable to selenium, has been hypothesized. Due to selenium’s high aggressiveness towards structural materials and based on economic feasibility, the use of low-alloy steel of ordinary quality for the technical design of the distillation process, instead of alloyed steel, has been thermodynamically justified. A method has been developed, and a device to refine selenium has been manufactured, which differs from existing ones by the inertial purification of the vapor phase from droplet suspension. The development is protected by a security document (patent KZ No. 37275). Based on the completed developments, an industrial prototype of such equipment has been designed and implemented in production. Full article

Basketball referees play a crucial role in game management, yet the physical and physiological demands placed on them during a game remain understudied. This study analyzed the workload of 35 group 1 referees during a U-18 Spanish championship, examining the effects of refereeing technique (two referees vs. three referees) and competition sex (male vs. female) across game quarters. Physical and physiological demands were measured using inertial devices and heart rate monitors during 37 matches (18 men’s and 19 women’s). The results revealed that 2-referee teams experienced significantly greater physical demands, covering approximately 25% more total distance and demonstrating higher values in high-intensity running compared to 3-referee teams. Female competition elicited higher demands in specific variables, particularly in the distance covered above 16 km/h and average speed. Analysis across quarters showed distinct temporal patterns, with the first and third quarters presenting the highest demands, especially for 2-referee teams. These findings suggest that basketball referees’ physical preparation should be tailored to the officiating technique and competition sex, with a particular emphasis on developing specific conditioning programs for the 2-referee technique and implementing targeted recovery strategies between quarters to maintain optimal performance throughout the game. Full article

Diabetic foot ulcers (DFUs) are a serious complication of diabetes, associated with high recurrence and amputation rates. Adherence to offloading devices is critical for wound healing but remains inadequately monitored in real-world settings. This study evaluates the SmartBoot edge-computing system—a wearable, real-time remote monitoring solution integrating an inertial measurement unit (Sensoria Core) and smartwatch—for its validity in quantifying cadence and step count as digital biomarkers of frailty, and for detecting adherence. Twelve healthy adults wore two types of removable offloading boots (Össur and Foot Defender) during walking tasks at varied speeds; system outputs were validated against a gold-standard wearable and compared with staff-recorded adherence logs. Additionally, user experience was assessed using the Technology Acceptance Model (TAM) in healthy participants (n = 12) and patients with DFU (n = 81). The SmartBoot demonstrated high accuracy in cadence and step count across conditions (bias < 5.5%), with an adherence detection accuracy of 96% (Össur) and 97% (Foot Defender). TAM results indicated strong user acceptance and perceived ease of use across both cohorts. These findings support the SmartBoot system’s potential as a valid, scalable solution for real-time remote monitoring of adherence and mobility in DFU management. Further clinical validation in ongoing studies involving DFU patients is underway. Full article

Background: Soccer performance is largely dependent on high-intensity, unilateral actions such as sprints, jumps, and changes of direction. These demands can lead to strength and power differences between limbs, highlighting the importance of individualised assessment in professional players. Rotational inertial devices offer a valuable method to evaluate and train these mechanical variables separately for each leg. The aim of this study was twofold: (a) to characterise the mechanical variables derived from several lower-body strength exercises performed on rotational inertial devices, all targeting the same muscle group; and (b) to compare the mechanical variables between the dominant and non-dominant leg for each exercise. Methods: Twenty-six male professional soccer players (age = 26.3 ± 5.1 years; height = 182.3 ± 0.6 cm; weight = 75.9 ± 5.9 kg; body mass index = 22.8 ± 1.1 kg/m²; fat mass percentage = 9.1 ± 0.6%; fat-free mass = 68.8 ± 5.3 kg), all belonging to the same professional Belgian team, voluntarily participated in this study. The players completed a single assessment session consisting of six unilateral exercises (i.e., quadriceps hip, hamstring knee, adductor, quadriceps knee, hamstring hip, and abductor). For each exercise, they performed two sets of eight repetitions with each leg (i.e., dominant and non-dominant) in a randomised order. Results: The quadriceps hip exercise resulted in higher mechanical values compared to the quadriceps knee exercise in both limbs (p < 0.004). Similarly, the hamstring hip exercise produced greater values across all variables and limbs (p < 0.004), except for peak force, where the hamstring knee exercise exhibited higher values (p < 0.004). The adductor exercise showed higher peak force values for the dominant limb (p < 0.004). The between-limb comparison revealed differences only in the abductor exercise (p < 0.004). Conclusions: These findings suggest the necessity of prioritising movement selection based on targeted outcomes, although it should be considered that the differences between limb differences are very limited. Full article

A rather novel approach for delivery of inertia-like grid services through energy storage devices is described and validated by physical experiments and on-site measurements. In this approach, denoted “amplified inertia response”, an actual inertial response from a grid-connected synchronous machine is amplified. This inertia emulation approach is contrasted by what is called synthetic inertia, which uses a frequency-locked loop in order to extract the grid frequency. The synthetic inertia faces the usual input signal filtering challenges if the signal-to-noise ratio is low. The amplified inertia controller avoids the input filtering since it only amplifies the natural inertial response from a synchronous machine. However, rotor angle oscillations lead to filtering requirements of the amplified version as well, but on the output signal of the controller. Experimental comparisons are conducted both on the measurement output from the physical experiments in a microgrid and on analysis based on input from on-site measurements from a 55 MVA hydropower generator connected to the Nordic grid. In the specific cases compared, we observe that the amplified inertia version is the better method for smaller power systems, with large frequency fluctuations. On the other hand, the synthetic inertia method is the better in larger power systems as compared to the amplification of the inertial response from a real production unit. Full article

Star sensors, as the most precise attitude measurement devices currently available, play a crucial role in spacecraft attitude estimation. However, traditional frame-based cameras tend to suffer from target blur and loss under high-dynamic maneuvers, which severely limit the applicability of conventional star sensors in complex space environments. In contrast, event cameras—drawing inspiration from biological vision—can capture brightness changes at ultrahigh speeds and output a series of asynchronous events, thereby demonstrating enormous potential for space detection applications. Based on this, this paper proposes an event data extraction method for weak, high-dynamic space targets to enhance the performance of event cameras in detecting space targets under high-dynamic maneuvers. In the target denoising phase, we fully consider the characteristics of space targets’ motion trajectories and optimize a classical spatiotemporal correlation filter, thereby significantly improving the signal-to-noise ratio for weak targets. During the target extraction stage, we introduce the DBSCAN clustering algorithm to achieve the subpixel-level extraction of target centroids. Moreover, to address issues of target trajectory distortion and data discontinuity in certain ultrahigh-dynamic scenarios, we construct a camera motion model based on real-time motion data from an inertial measurement unit (IMU) and utilize it to effectively compensate for and correct the target’s trajectory. Finally, a ground-based simulation system is established to validate the applicability and superior performance of the proposed method in real-world scenarios. Full article

Parkinson’s disease (PD) is a neurodegenerative disorder commonly marked by upper limb tremors that interfere with daily activities. Wearable devices, such as smartwatches, represent a promising solution for continuous and objective monitoring in PD. This study aimed to develop and validate a tremor-detection algorithm using smartwatch sensors. Data were collected from 21 individuals with PD and 27 healthy controls using both a commercial inertial measurement unit (G-Sensor, BTS Bioengineering, Italy) and a smartwatch (Apple Watch Series 3). Participants performed standardized arm movements while sensor signals were synchronized and processed to extract relevant features. Statistical analyses assessed discriminant and concurrent validity, reliability, and accuracy. The algorithm demonstrated moderate to strong correlations between smartwatch and commercial IMU data, effectively distinguishing individuals with PD from healthy controls showing associations with clinical measures, such as the MDS-UPDRS III. Reliability analysis demonstrated agreement between repeated measurements, although a proportional bias was noted. Power spectral density (PSD) analysis of accelerometer and gyroscope data along the x-axis successfully detected the presence of tremors. These findings support the use of smartwatches as a tool for detecting tremors in PD. However, further studies involving larger and more clinically impaired samples are needed to confirm the robustness and generalizability of these results. Full article

This study proposes a novel heart rate estimation method that detects subtle cardiac-induced vibrations propagated through the cardiovascular system based on the ballistocardiography (BCG) principle, using a six-axis heart rate sensing device that integrates a three-axis accelerometer and a three-axis gyroscope. To validate the effectiveness of the proposed method, a comparative analysis was conducted against heart rate measurements obtained from photoplethysmography (PPG) sensors, which are widely used in conventional heart rate monitoring. Experiments were conducted on 20 adult participants, and frequency domain analysis was performed using different time windows of 30 s, 20 s, 8 s, and 4 s. The results showed that the 4 s window provided the highest accuracy in heart rate estimation, demonstrating that the proposed method can effectively capture fine cardiac-induced vibrations. This approach offers a significant advantage by utilizing inertial sensors commonly embedded in wearable devices for heart rate monitoring without the need for additional optical sensors. Compared to optical-based systems, the proposed method is more power-efficient and less affected by environmental factors such as ambient lighting conditions. The findings suggest that heart rate estimation using the six-axis heart rate sensing device presents a reliable, continuous, and non-invasive alternative for cardiovascular monitoring. Full article

Camera-centric perception has matured into a cornerstone of modern autonomy, from self-driving cars and factory cobots to underwater and planetary exploration. This review synthesizes more than a decade of progress in vision-based robotic navigation through an engineering lens, charting the full pipeline from sensing to deployment. We first examine the expanding sensor palette—monocular and multi-camera rigs, stereo and RGB-D devices, LiDAR–camera hybrids, event cameras, and infrared systems—highlighting the complementary operating envelopes and the rise of learning-based depth inference. The advances in visual localization and mapping are then analyzed, contrasting sparse and dense SLAM approaches, as well as monocular, stereo, and visual–inertial formulations. Additional topics include loop closure, semantic mapping, and LiDAR–visual–inertial fusion, which enables drift-free operation in dynamic environments. Building on these foundations, we review the navigation and control strategies, spanning classical planning, reinforcement and imitation learning, hybrid topological–metric memories, and emerging visual language guidance. Application case studies—autonomous driving, industrial manipulation, autonomous underwater vehicles, planetary rovers, aerial drones, and humanoids—demonstrate how tailored sensor suites and algorithms meet domain-specific constraints. Finally, the future research trajectories are distilled: generative AI for synthetic training data and scene completion; high-density 3D perception with solid-state LiDAR and neural implicit representations; event-based vision for ultra-fast control; and human-centric autonomy in next-generation robots. By providing a unified taxonomy, a comparative analysis, and engineering guidelines, this review aims to inform researchers and practitioners designing robust, scalable, vision-driven robotic systems. Full article

Orthotics are often used to support the metacarpophalangeal joint (MCPj) in horses recovering from soft tissue injury; however, their effect on the MCPj biomechanics remain largely underexplored. The MCPj moves primarily in the sagittal plane, flexing during the swing phase and extending during the stance phase. The suspensory ligament and flexor tendons act as biological springs resisting MCPj extension. Injuries to these structures are common and, although early mobilization promotes their healing, controlled loading may be beneficial during rehabilitation. This study aims to evaluate the efficacy of a semirigid orthotic in limiting the MCPj extension and the MCPj range of motion, and its influence on the MCPj kinematics. Twelve healthy horses were equipped with portable inertial sensors on the distal limb. The MCPj extension and the MCPj range of motion were assessed during walking and trotting without the orthotic (S0) and with the orthotic using two different support settings (S1 and S4). Data were evaluated for normality and homoscedasticity. A Student t-test was used to compare the MCPj angle pattern of the two forelimbs of each horse at the baseline. Data were analysed using one-way ANOVA to compare the mean values across conditions, followed by paired t-tests for post-hoc comparison (significance set at p < 0.05). The results showed significant reductions in both the MCPj extension and the MCPj range of motion, with the greatest restriction occurring at the highest support setting. These results suggest that the semirigid orthotic limits the MCPj movement in the sagittal plane and consequently the load on the suspensory ligament and flexor tendons. Therefore, this orthotic device is an effective tool during rehabilitation for forelimb tendon and ligament injuries. Full article

Background/Objectives: Power indices may provide valuable information for performance and injury prevention in soccer players, so increasing the knowledge about them seems essential. Therefore, this study aimed to establish limb-specific normative values for flywheel-derived power indices in professional soccer players, while accounting for limb performance or ability, to explore the relationships between power indices across variables and to compare the power outcomes related to these indices between injured and non-injured players within four months post-assessment. Methods: Twenty-two male professional soccer players (age: 26.6 ± 4.6 years; competitive level: Belgian second division) were recruited from a single elite-tier club to participate in this cross-sectional diagnostic study. Participants underwent a standardized assessment protocol, executed in a rotational inertial device, comprising six unilateral exercises focused on the lower limbs: hip-dominant quadriceps (Qhip), knee-dominant quadriceps (Qknee), hip-dominant hamstrings (Hhip), knee-dominant hamstrings (Hknee), adductor (Add), and abductor (Abd). The testing session incorporated a randomized, counterbalanced design, with each exercise comprising two sets of eight maximal concentric–eccentric repetitions per limb. Leg dominance was operationally defined as the self-reported preferred limb for ball-striking tasks. Power indices were calculated from these exercises. Results: No significant differences in flywheel-derived power indices were found between limbs or between injured and non-injured players. However, significant correlations between indices were found in all power variables, with the Qhip:Qknee and Hhip:Hknee concentric ratios emerging as the most clinically actionable biomarkers for rapid screening. Conclusions: These results suggest the necessity of including more variables for injury prediction. Moreover, power indices could be considered based on the classification of limbs as “strong” or “weak”. Full article