BackgroundOverhead crane operators are exposed to a high risk of musculoskeletal disorders (MSDs), partly due to poorly fitted cab seat designs that do not match operator anthropometry.ObjectiveThis study examined the mismatch between cab seat dimensions and the anthropometric characteristics of crane operators and proposed an ergonomic redesign to reduce MSD risks.MethodsSixty-four operators were evaluated using the Rapid Upper Limb Assessment (RULA) method during eight key tasks. Anthropometric measurements were compared with existing seat dimensions. A new seat was modelled in 3D MAX software, incorporating operator anthropometry.ResultsSignificant mismatches were identified in seat height, handle height, backrest width, seat depth, and backrest height. The proposed design included a seat height of 41-56 cm, a width of 47 cm, a depth of 53 cm, and a head/neck support height of 108 cm. Simulation showed that the redesigned seat reduced RULA risk scores from 4 (high risk) to 1 (low risk).ConclusionThe findings demonstrate the importance of integrating ergonomic and anthropometric principles into cab seat design. The redesigned seat offers improved postural support, reduces MSD risk, and may enhance operator comfort and performance.

Background: This pilot clinical study aimed to evaluate the mandibular position at the maximum intercuspal position (MIP) obtained with a virtual interocclusal record using an intraoral scanner across different dental chair backrest inclinations, in order to establish a protocol for future larger studies. Methods: In this single-center pilot study, 10 fully dentate participants underwent maxillary and mandibular full-arch intraoral scans. Virtual interocclusal records at MIP were obtained with an intraoral scanner at three dental chair backrest inclinations (90, 120, and 180 degrees). Conventional vinyl polysiloxane interocclusal records were made at the same inclinations. All scans were printed into physical models and mounted using the conventional records. Digitized casts and intraoral scans were superimposed onto a single common reference, the virtually mounted 90-degree scan, using metrology software. Because all deviations were expressed relative to that reference, the virtual 90-degree condition is zero by construction and was excluded as a data level from inferential models. Separate linear mixed-effects models were fitted for each translation and rotation axis, with participant as a random intercept and recording method, inclination, and their interaction as fixed effects; p values were Holm-adjusted across the six axes. Equivalence was explored with two one-sided tests against margins of ±0.5 mm and ±1.0 degrees; because these margins were specified post hoc, the equivalence analysis is exploratory. Results: Chair inclination did not detectably affect either recording method: no inclination main effect or method × inclination interaction survived multiplicity correction, and virtual records at 120 and 180 degrees differed by no more than 0.05 mm and 0.08 degrees. Recording method did differ. Conventional records were displaced relative to virtual records by 0.27 mm along the Y axis (95% CI 0.19 to 0.34; Holm-adjusted p < 0.001), in the same direction in 9 of 10 participants. The corresponding X-axis offset was 0.23 mm (95% CI 0.06 to 0.40) and did not survive multiplicity correction in the primary analysis (Holm-adjusted p = 0.060). The exploratory equivalence criterion was met, that is, the 90% confidence interval fell entirely within the post hoc equivalence margin, for 11 of 18 method × inclination comparisons, rising to 16 of 18 in the sensitivity analysis. Conclusions: In this pilot sample, no statistically detectable effect of dental chair backrest inclination between 90 and 180 degrees on the recorded mandibular position at MIP was observed for either recording method in healthy, fully dentate individuals; virtual and conventional records met the exploratory post hoc equivalence criterion in most rotational axes but showed a small, systematic translational offset of approximately 0.23 to 0.31 mm, most clearly along the Y axis. These preliminary findings require confirmation in a larger, prospectively powered and randomized equivalence trial with a prospectively defined equivalence margin.

BackgroundModern vehicle seats often include adjustable features that let passengers customize their seating positions to improve their experience. One key feature is the headrest, which can be adjusted to accommodate passengers of different sizes and preferences. However, limited studies have quantitatively examined human-seat interaction in the head-neck region, accounting for different anthropometric characteristics and backrest seat configurations.ObjectiveThe research objective is to develop a computational approach to predict human-headrest interaction, enabling a quantitative assessment of headrest configurations.MethodThis study developed a computational framework based on multibody dynamics to simulate human-seat interaction, including solutions for sitting posture kinematics and for predicting headrest-supporting force across various seating conditions. Seating tests were conducted with 25 subjects to validate the proposed approach.ResultsThe model showed a strong correlation with experimental measurements of headrest supporting force (ρ = 0.872) at the user-selected headrest position. The results support the application of the proposed model in predicting head-headrest interaction and the external loading conditions of the head-neck region.ConclusionsA multibody human-seat interaction model was developed and validated. It predicts headrest supporting forces consistent with experimental measurement. The framework enables efficient analysis of reclined headrest interactions and supports rapid evaluation and customization of designs across seating conditions and users.

Ergonomics research increasingly prioritises driver comfort in complex vibration environments for safety and health. The existing evaluation methods fail to reveal the nonlinear relationship between vibration and comfort, ignoring the interpretability. This study proposes an interpretability comfort evaluation method using a hierarchical double path attention network (HDPA-Net). First, the acceleration and comfort data of the seat floor, cushion and backrest are collected through the road test. Then, the vibration transfer model and path decoupling method are utilised to identify vibration-sensitive paths. Finally, combined with a deep-learning model for comfort evaluation. The results showed that the multi-axis coupling has a significant impact on the transmission path. The HDPA-Net can capture vibration characteristics, achieving a mean absolute error of 3.3073 within a 0-100 score range, below the 10% acceptance threshold of ergonomics experts. This provides a new method for comfort evaluation and has an important guiding value for ergonomic seat design.

Electric vehicles (EVs) are moving toward greater intelligence and personalization, but the dynamic adaptability of current vehicle seats no longer meets drivers' comfort and safety needs. To address insufficient posture adaptation and low recognition accuracy for occluded joints, this study proposes an intelligent seat adaptive adjustment model on the basis of human pose recognition. Kinect V2 was used to collect drivers' posture data, and features were extracted through a cascaded pose analysis network (PSN) integrating a spatial transformer network, squeeze-and-excitation module, and convolutional block attention module. The network recognized 16 joint points with an average accuracy of 0.87, a PCK@0.2 (percentage of correct keypoints within 20% of limb length) of 0.92, and a mean per joint position error (MPJPE) of 3.2 mm. Considering biomechanical and vehicle physical constraints, a seat adjustment model was established and optimized using the analytic hierarchy process (AHP) to coordinate seat fore-aft position, height, and backrest angle. Simulated driving experiments suggested preliminary effectiveness: Subjective comfort increased by about 30%, lumbar muscle activity decreased by 39.5%, and posture estimation plus parameter generation remained within 0.3 s. These findings indicate preliminary feasibility for intelligent seat posture assistance under simulated conditions, whereas practical safety validation in real driving conditions remains for future work.

Recumbent cycling provides an adjustable configuration in which backrest angle and crank-axis height can alter lower-limb loading. Backrest angle changes the orientation of the active musculature relative to gravity, whereas crank-axis height modifies the foot-pedal interface and the ankle lever arm. Whether such positioning is associated with differences in lower-limb electromyographic (EMG) activation across both factors together has not been examined. Using a randomized crossover design, fifty-nine healthy young men cycled at 100 W and 50 rpm under four conditions combining two backrest angles (30°, 75°) and two crank-axis heights (Rh, high, 77 cm; Rl, low, 45 cm). Surface EMG from the rectus femoris (RF), biceps femoris (BF), and gastrocnemius medialis (GAS) was analyzed for root mean square (RMS) amplitude, absolute onset sequence, and relative recruitment timing (%Sequence, derived using Telescan software and referenced to RF). RMS amplitude did not differ across conditions for any muscle (all p ≥ 0.356), and absolute onset sequence showed no condition effect (all p ≥ 0.197). For GAS %Sequence, the Greenhouse-Geisser-corrected omnibus test was significant (F(1.32, 76.56) = 28.45, p < 0.001), driven by a within-30° contrast in which %Sequence was lower under Rl than Rh (paired t(58) = 10.39, Holm-adjusted p < 0.0001; mean difference 22.0 percentage points, 95 % CI [17.8, 26.3]; dz = 1.35). Because %Sequence is referenced to RF, this exploratory shift should be interpreted cautiously. Lower-limb activation may be constrained by the closed-chain nature of pedaling, whereas distal recruitment timing may be sensitive to crank-axis height and the foot-pedal interface.

Occupational whole-body vibration (WBV) exposure can result in back injuries, with females at greater risk. Transmissibility is one way to quantify injury risk; it is measured using accelerometers and defined in the basicentric coordinate system (BCS). The internal axes of accelerometers at the sacrum (S1) and thoracic spine (T6) have been shown to deviate from the BCS dependent on sex, however, the effects on transmissibility are unknown. This work aimed to compare original and corrected transmissibility, and to investigate sex differences at S1 and T6. 17 males and 22 females were exposed to vertical sinusoidal vibration while sitting on a rigid seat with no backrest. Four orthogonal motion capture markers were attached to accelerometers at S1 and T6 to correct acceleration data to the BCS. Transmissibility was calculated using original and corrected accelerations. Differences were examined using a mixed factorial ANOVA. At T6, females had larger (p = 0.031) vertical transmissibility, and sex differences were larger with corrected accelerations. At S1, female vertical transmissibility at resonance was 1.5 times larger (p = 0.007) than males. Cross-axis transmissibility at S1 was larger (p = 0.008) with corrected accelerations. Females experienced greater S1 cross-axis transmissibility at all frequencies, and sex differences were greater with corrected accelerations. Larger cross-axis transmissibility with corrected accelerations suggests that fore-aft spine motion is underestimated when acceleration data aren't corrected, highlighting the importance of accounting for accelerometer orientation. Moreover, despite exposure to the same input vibration, females experienced greater vibration transmission through the spine, which may be associated with higher compressive and shear forces.

Autonomous UVC-based disinfection robots have gained widespread use after the COVID-19 outbreak to limit infectious disease transmission. Although several semi-automatic and fully automatic UVC robots are employed for surface disinfection in high-risk areas, their efficacy is restricted because they cannot disinfect complex regions of contaminated surfaces that are distant, located at different heights, in narrow pathways, or within shadow zones. This paper reports the design, development, and implementation of a Robotic Disinfection System with Movable Ultraviolet Light Radiating Arms (RwMA) to address these limitations. To quantify the performance of RwMA, a simulated inactivation study using an extended UVC irradiance model and experiments were conducted, and results were compared with a conventional UVC-based Disinfection Robot without Movable Arms (RoMA). The simulated study quantified UVC irradiance and pathogen inactivation time of RwMA and RoMA for commonly contaminated surfaces such as "Chair Back," "Chair Seat," "Chair Armrest," and "Chair Backrest" while disinfecting a row of chairs. RwMA delivered high and nearly uniform irradiance on all chair surfaces, whereas RoMA produced extremely low irradiance that further decreased for distant chairs due to distance and shadowing. For 4-5 log inactivation of bacteriophage MS2 on a row of chairs, RwMA required only 11.873 s, whereas RoMA needed 418.223 s (6.97 min), which is significantly higher. As anticipated by simulated studies, experimental evaluation using bacteriophage MS2 confirmed consistently higher and more uniform infectivity reduction by RwMA across all near and distant chair positions, unlike RoMA. These results support the adoption of RwMA for rapid and effective disinfection in shared environments.