Angular Error Research Articles

CGLight: An effective indoor illumination estimation method based on improved convmixer and GauGAN

Illumination consistency is a key factor for seamlessly integrating virtual objects with real scenes in augmented reality (AR) systems. High dynamic range (HDR) panoramic images are widely used to estimate scene lighting accurately. However, generating environment maps requires complex deep network architectures, which cannot operate on devices with limited memory space. To address this issue, this paper proposes CGLight, an effective illumination estimation method that predicts HDR panoramic environment maps from a single limited field-of-view (LFOV) image. We first design a CMAtten encoder to extract features from input images, which learns the spherical harmonic (SH) lighting representation with fewer model parameters. Guided by the lighting parameters, we train a generative adversarial network (GAN) to generate HDR environment maps. In addition, to enrich lighting details and reduce training time, we specifically introduce the color consistency loss and independent discriminator, considering the impact of color properties on the lighting estimation task while improving computational efficiency. Furthermore, the effectiveness of CGLight is verified by relighting virtual objects using the predicted environment maps, and the root mean square error and angular error are 0.0494 and 4.0607 in the gray diffuse sphere, respectively. Extensive experiments and analyses demonstrate that CGLight achieves a balance between indoor illumination estimation accuracy and resource efficiency, attaining higher accuracy with nearly 4 times fewer model parameters than the ViT-B16 model.

An Investigation of Multimodal Kinematic Template Matching for Ray Pointing Prediction for Target Selection in VR

We explore the use of multimodal input to predict the landing position of a ray pointer while selecting targets in a virtual reality (VR) environment. We first extend a prior 2D Kinematic Template Matching technique to include head movements. This new technique, Head-Coupled Kinematic Template Matching, was found to improve upon the existing 2D approach, with an angular error of 10.0° when a user was 40% of the way through their movement. We then investigate two additional models that incorporated eye gaze, which were both found to further improve the predicted landing positions. The first model, Gaze-Coupled Kinematic Template Matching resulted in angular error of 6.8° for reciprocal target layouts and 9.1° for random target layouts, when a user was 40% of the way through their movement. The second model, Hybrid Kinematic Template Matching, resulted in angular error of 5.2° for reciprocal target layouts and 7.2° for random target layouts when a user was 40% of the way through their movement. We also found that using just the current gaze location resulted in sufficient predictions in many conditions. We reflect on our results by discussing the broader implications of utilizing multimodal input to inform selection predictions in VR.

Feasibility of augmented reality using dental arch-based registration applied to navigation in mandibular distraction osteogenesis: a phantom experiment

ObjectiveDistraction osteogenesis is a primary treatment for severe mandibular hypoplasia. Achieving the ideal mandible movement direction through precise distraction vector control is still a challenge in this surgery. Therefore, the aim of this study was to apply Optical See-Through (OST) Augmented Reality (AR) technology for intraoperative navigation during mandibular distractor installation and analyze the feasibility to evaluate the effectiveness of AR in a phantom experiment.MethodsPhantom was made of 3D-printed mandibular models based on preoperative CT scans and dental arch scans of real patients. Ten sets of 3D-printed mandible models were included in this study, with each set consisting of two identical mandible models assigned to the AR group and free-hand group. 10 sets of mandibular distraction osteogenesis surgical plans were designed using software, and the same set of plans was shared between the AR and free-hand groups. Surgeons performed bilateral mandibular distraction osteogenesis tasks under the guidance of AR navigation, or the reference of the preoperative surgical plan displayed on the computer screen. The differences in angular errors of distraction vectors and the distance errors of distractor positions under the guidance of the two methods were analyzed and compared.Results40 distractors were implanted in both groups, with 20 cases in each. In intra-group comparisons between the left and right sides, the AR group exhibited a three-dimensional spatial angle error of 1.88 (0.59, 2.48) on the left and 2.71 (1.33, 3.55) on the right, with P = 0.085, indicating no significant bias in guiding surgery on both sides of the mandible. In comparisons between the AR group and the traditional free-hand (FH) group, the average angle error was 1.94 (1.30, 2.93) in the AR group and 5.06 (3.61, 9.22) in the free-hand group, with P < 0.0001, resulting in a 61.6% improvement in accuracy. The average displacement error was 1.53 ± 0.54 mm in the AR group and 3.56 ± 1.89 mm in the free-hand group, with P < 0.0001, indicating a 57% improvement in accuracy.ConclusionAugmented Reality technology for intraoperative navigation in mandibular distraction osteogenesis is accurate and feasible. A large randomized controlled trial with long-term follow-up is needed to confirm these findings.Trial RegistrationThe project has been registered with the Chinese Clinical Trial Registry, with registration number ChiCTR2300068417. Date of Registration: 17 February 2023.

Modeling and Simulation of Wide-Frequency Characteristics of Electromagnetic Standard Voltage Transformer

To achieve the broadband applicability of standard voltage transformers in “dual high” power systems, an equivalent circuit model of the standard voltage transformer is first established. Using the complex magnetic permeability method and utilizing existing core parameters, the excitation impedance values are obtained. Next, based on the equivalent circuit model, the no-load error function of the standard voltage transformer is analyzed, and through simulation, the no-load error response curve of the standard voltage transformer in the frequency range of 20 Hz to 3000 Hz is derived. The simulation results indicate that within the 20 Hz to 700 Hz range, both the no-load ratio error and the no-load angular error meet the accuracy requirements, with the ratio error within ±0.05% and the angular error within 2′. Additionally, the derivation of the error transfer function demonstrates the correlation between the no-load error values and the number of turns and cross-sectional area of the standard voltage transformer. Simulation results, obtained by increasing and decreasing the number of turns and cross-sectional area by 10%, provide valuable insights for the error compensation and structural design of standard voltage transformers.

Augmented reality guidance improves accuracy of orthopedic drilling procedures

In several orthopedic procedures, the accurate use of surgical power tools is critical to avoid damage to surrounding tissues. As such, various guidance techniques and safety measures were developed. Augmented reality (AR) guidance shows promise but requires validation. We evaluated a new approach using an inside-out infrared tracking solution for the HoloLens to compensate for its limited tracking performance. Eighteen participants with varying levels of experience (student, trainee, expert) each drilled twelve trajectories (six perpendicular, six oblique) in equidimensional wooden logs. Three different techniques were evaluated: freehand drilling; proprioception-guided drilling towards the contralateral index finger; and AR-guided drilling using a tracked drill and a virtual overlay of the log with predefined guidance vectors. The angular errors between planned and performed trajectories were compared using a mixed-design ANOVA. The results demonstrated that guidance technique (p < 0.001) and drilling direction (p < 0.001) significantly affected drilling accuracy, while experience (p = 0.75) did not. AR outperformed both other techniques, particularly for oblique trajectories (p < 0.001). For perpendicular trajectories, it only outperformed proprioception guidance (p = 0.04). Target plots revealed an important scatter perpendicular to the longitudinal axis of the log during freehand and proprioception-guided drilling, especially for oblique trajectories. This inaccuracy disappeared during AR-guided drilling. As such, we were able to conclude that AR guidance using inside-out infrared tracking reduced angular uncertainty during directional drilling, resulting in improved drilling accuracy. This improvement was particularly noticeable for complex trajectories and angles. The benefits of AR guidance were observed across all experience levels, highlighting its potential for orthopedic applications. We believe this study opens the way for the methodical evaluation of AR guidance in specific orthopedic use cases.

Position and orientation estimation method based on 3D digital morphology contour registration

Abstract Accurately and quickly obtaining the positions and orientations of mechanical parts based on the digital morphologies of mechanical parts are the key to achieving efficient and accurate assembly of mechanical parts. However, due to poor robustness and compactness in extracting digital morphology contours of mechanical parts, the accuracy of assembly positions and orientations obtained by using digital morphology contours cannot meet the requirements of high-precision assembly. Therefore, this paper proposes a position and orientation estimation method based on 3D digital morphology contour registration. This method extracts and optimizes digital morphology contours of mechanical parts and obtains the assembly positions and orientations by using an improved iterative closest point method to register the extracted digital morphology contours with those of the mechanical parts in assembly targets with desired positions and orientations. Experiments are conducted using mechanical parts from the ABC dataset and inertial confinement fusion micro-target. From the experimental results, when using the assembly positions and orientations obtained through the method proposed in this paper to assemble mechanical parts, it can achieve translation absolute errors of 8 μm, 5 μm, and 9 μm along the X-, Y-, and Z-axes, respectively. Similarly, the angular absolute errors in rotations around the Z-, Y-, and X-axes can be less than or equal to 0.16°, 0.15°, and 0.11°, respectively. The results prove that the proposed method in this paper exhibits high computational efficiency and accuracy, providing an effective approach for digital assembly of mechanical parts.

Adaptive prescribed performance control for spacecraft attitude synchronization subject to external disturbances with guaranteed steady‐state performance

AbstractThis paper proposes an adaptive prescribed performance control approach for multiple spacecraft attitude synchronization with the undirected topology. A novel distributed observer is proposed to estimate the states of the leader spacecraft while the estimation value of attitude is still a unit quaternion. Then we design the adaptive prescribed performance control algorithm restrain the external disturbances and parameter uncertainty. By the unit quaternion estimation value of attitude, we make the extension from single spacecraft to multiple spacecraft. Compared to some previous results, the bounds of attitude tracking error and angular velocity error in the steady state can be adjusted by users.

The effect of the angular error on the determination of the sound power levels of industrial coolers

Drycoolers are relevant noise sources in many industrial plants due to their typically exposed positioning. For this reason, drycoolers are often subject to strict acoustic requirements in the form of maximum permissible sound power levels. Thus, the suppliers have to provide proof of compliance with these requirements before delivery. The acoustic verification measurement is usually carried out by measuring the sound pressure level using the enveloping surface method in accordance with EN 13487. According to EN 13487, the measurement is carried out at discrete points on a cuboid measuring surface. Since drycoolers are sound sources that extend over a large area, an angular error occurs when measuring sound pressure levels on a cuboid measuring surface, which leads to a superelevation of the measured sound pressure level, since the acoustic particle velocity on the cuboid measuring surface is not perpendicular to the measuring surface at almost any point. Therefore, the sound power level determined is methodically too high. By measuring the sound intensity levels in accordance with ISO 9614-2 instead of the sound pressure levels, the influence of this angular error can be excluded and brought into good agreement with theoretical considerations and calculations of the angular error.

Tunable graphene plasmonic metadevice for infrared polarization resolved spectroscopy detection

Polarization-resolved spectroscopy imaging holds significant promise in various fields. However, conventional polarization-resolved spectroscopy imaging systems often reply on separate dispersion elements, polarization splitting components, and mechanical scanning or rotating structures, resulting in bulky systems with intricate designs. The pursuit of lightweight and seamlessly integrated polarization spectroscopy imaging systems presents a critical challenge. Here, we propose an integrated polarization spectroscopy detector operating in the mid-infrared range based on a tunable graphene metasurface. Within the graphene metasurface, plasmonic resonances of graphene are excited by a gold nano-grating, allowing simultaneous modulation of spectral and polarization transmission characteristics for infrared light by tuning the Fermi energy of graphene. With the help of neural network based recovery algorithms, this system achieves pixel-level spectral detection (with a resolution below 200 nm), multi-color polarization Stokes vector analysis (with a monochromatic angular error of less than 0.1 rad), and concurrent polarization and spectroscopy detection. This research paves the way for the development of the next generation integrated infrared polarization resolved spectroscopy imaging systems.

FHLight: A novel method of indoor scene illumination estimation using improved loss function

In augmented reality tasks, especially in indoor scenes, achieving illumination consistency between virtual objects and real environments is a critical challenge. Currently, mainstream methods are illumination parameters regression and illumination map generation. Among these two categories of methods, few works can effectively recover both high-frequency and low-frequency illumination information within indoor scenes. In this work, we argue that effective restoration of low-frequency illumination information forms the foundation for capturing high-frequency illumination details. In this way, we propose a novel illumination estimation method called FHLight. Technically, we use a low-frequency spherical harmonic irradiance map (LFSHIM) restored by the low-frequency illumination regression network (LFIRN) as prior information to guide the high-frequency illumination generator (HFIG) to restore the illumination map. Furthermore, we suggest an improved loss function to optimize the network training procedure, ensuring that the model accurately restores both low-frequency and high-frequency illumination information within the scene. We compare FHLight with several competitive methods, and the results demonstrate significant improvements in metrics such as RMSE, si-RMSE, and Angular error. In addition, visual experiments further confirm that FHLight is capable of generating scene illumination maps with genuine frequencies, effectively resolving the illumination consistency issue between virtual objects and real scenes. The code is available at https://github.com/WA-tyro/FHLight.git.

Drifted Uncertainty Evaluation of a Compact Machine Tool Spindle Error Measurement System

The accurate measurement of spindle errors, especially quasi-static errors, is one of the key issues for the analysis and compensation of machine tool thermal errors in machining accuracy. To quantitatively analyze the influence of the measurement system’s own drift on the measurement results, a drifted uncertainty evaluation method of the precision instrument considering the time drift coefficient is proposed. This study also produced a high-precision compact spindle error measurement device (with a displacement measurement error of less than ±1.33 μm and an angular measurement error of less than ±1.42 arcsecs) as the research object to verify the proposed drift uncertainty evaluation method. A method for evaluating the drift uncertainty of the measurement system is proposed to quantitatively evaluate the system error and drift uncertainty of the measurement device. Experiments show that the drift uncertainty evaluation method proposed in this paper is more suitable for evaluating the uncertainty changes in measurement instruments during long-term measurements compared to traditional methods.

Development of a high-precision long trace profiler utilizing shear measurements.

Compensating for the pitch error in the scanning movement is a fundamental issue when conducting large-scale surface shape measurements with deflectometric profilers. This paper presents a new long trace profiler employing a shearing measurement technique. In this setup, the optical head and the mirror under test are mounted on two independent parallel movable air-bearing carriages to enable shearing and scanning movements separately. The distance between the optical head and the tested mirror remains fixed, effectively minimizing the influence of system errors resulting from imperfections in optical devices. Simulation studies show that the double shear measurement method with a low-spatial-frequency filtering process can effectively mitigate high-frequency angular measurement errors introduced by the instability of the air-bearing stage. Experimental tests conducted on flat mirrors demonstrated a precision of less than 50 nrad rms, thereby confirming the robustness of the system.

Successful ACL repair by dynamic intraligamentary stabilisation is non-inferior in functional performance and worse in proprioception compared to healthy controls in a case-matched study.

The primary aim of this study was to assess non-inferiority in functional performance of the knee after dynamic intraligamentary stabilisation (DIS) surgery at a minimal follow-up of 1 year compared to healthy controls, based on limb symmetry index (LSI) of the single leg hop test (SLH). Additionally, functional performance based on the single leg triple hop test (SLTH) and side hop test (SH), proprioception and subjective outcome were evaluated. A total of 45 DIS patients were 1-to-1 matched to a healthy control. Functional performance was evaluated by LSI and absolute values on the SLH, SLTH and SH. Proprioception was assessed by joint position sense (JPS) test and International Knee Documentation Committee (IKDC) scores were obtained. Non-inferiority in functional performance after DIS compared to healthy controls was confirmed based on the mean LSI of the SLH and SLTH (97.6% vs. 99.6% and 97.5% vs. 100.6%, respectively) and non-confirmed on the SH (98.8% vs. 100.0%, respectively). No significant differences were found in absolute value of the SLH and SLTH and a significantly higher absolute value of the SH was found in the DIS group (p = 0.01). JPS absolute angular error was significantly higher in the DIS group compared to the control group (p = 0.01). The median IKDC score of the DIS group was significantly lower (92, IQR 85-95) than the control group (100, IQR 99-100), p < 0.001. In conclusion, functional performance after DIS was confirmed non-inferior compared to healthy controls based on the SLH and SLTH, although non-confirmed on the SH. Level III.

AI-smartphone markerless motion capturing of hip, knee, and ankle joint kinematics during countermovement jumps.

Recently, AI-driven skeleton reconstruction tools that use multistage computer vision pipelines were designed to estimate 3D kinematics from 2D video sequences. In the present study, we validated a novel markerless, smartphone video-based artificial intelligence (AI) motion capture system for hip, knee, and ankle angles during countermovement jumps (CMJs). Eleven participants performed six CMJs. We used 2D videos created by a smartphone (Apple iPhone X, 4K, 60 fps) to create 24 different keypoints, which together built a full skeleton including joints and their connections. Body parts and skeletal keypoints were localized by calculating confidence maps using a multilevel convolutional neural network that integrated both spatial and temporal features. We calculated hip, knee, and ankle angles in the sagittal plane and compared it with the angles measured by a VICON system. We calculated the correlation between both method's angular progressions, mean squared error (MSE), mean average error (MAE), and the maximum and minimum angular error and run statistical parametric mapping (SPM) analysis. Pearson correlation coefficients (r) for hip, knee, and ankle angular progressions in the sagittal plane during the entire movement were 0.96, 0.99, and 0.87, respectively. SPM group-analysis revealed some significant differences only for ankle angular progression. MSE was below 5.7°, MAE was below 4.5°, and error for maximum amplitudes was below 3.2°. The smartphone AI motion capture system with the trained multistage computer vision pipeline was able to detect, especially hip and knee angles in the sagittal plane during CMJs with high precision from a frontal view only.

A Multivariate Approach to Quantifying Risk Factors Impacting Stereotactic Robotic-Guided Stereoelectroencephalography.

Stereoelectroencephalography (SEEG) is an important method for invasive monitoring to establish surgical candidacy in approximately half of refractory epilepsy patients. Identifying factors affecting lead placement can mitigate potential surgical risks. This study applies multivariate analyses to identify perioperative factors affecting stereotactic electrode placement. We collected registration and accuracy data for consecutive patients undergoing SEEG implantation between May 2022 and November 2023. Stereotactic robotic guidance, using intraoperative imaging and a novel frame-based fiducial, was used for planning and SEEG implantation. Entry-point (EE), target-point (TE), and angular errors were measured, and statistical univariate and multivariate linear regression analyses were performed. Twenty-seven refractory epilepsy patients (aged 15-57 years) undergoing SEEG were reviewed. Sixteen patients had unilateral implantation (10 left-sided, 6 right-sided); 11 patients underwent bilateral implantation. The mean number of electrodes per patient was 18 (SD = 3) with an average registration mean error of 0.768 mm (SD = 0.108). Overall, 486 electrodes were reviewed. Univariate analysis showed significant correlations of lead error with skull thickness (EE: P = .003; TE: P = .012); entry angle (EE: P < .001; TE: P < .001; angular error: P = .030); lead length (TE: P = .020); and order of electrode implantation (EE: P = .003; TE: P = .001). Three multiple linear regression models were used. All models featured predictors of implantation region (157 temporal, 241 frontal, 79 parietal, 9 occipital); skull thickness (mean = 5.80 mm, SD = 2.97 mm); order (range: 1-23); and entry angle in degrees (mean = 75.47, SD = 11.66). EE and TE error models additionally incorporated lead length (mean = 44.08 mm, SD = 13.90 mm) as a predictor. Implantation region and entry angle were significant predictors of error (P ≤ .05). Our study identified 2 primary predictors of SEEG lead error, region of implantation and entry angle, with nonsignificant contributions from lead length or order of electrode placement. Future considerations for SEEG may consider varying regional approaches and angles for more optimal accuracy in lead placement.

Research on angular displacement detection technology of inter-satellite laser communication based on coherent system

With the rapid development of spatial information networks technologies, inter-satellite laser communication links have played an important role in the satellite Internet. High-precision relative angular displacement detection is the foundation for achieving real-time tracking of laser communication links, and its accuracy directly impacts the tracking performance and communication quality of the laser communication link. Traditional laser communication systems utilize intensity-based position detection methods to calculate angular displacement, requiring setting separate Charge Coupled Device (CCD) or Four-quadrant Detector (QD) as well as independent optical tracking branches. This setup makes it difficult to integrate with high-speed coherent communication systems. Additionally, the method employing intensity detection to determine angular displacement based on spot position has lower accuracy in theory. A angular displacement detection of coherent-based inter-satellite laser communication is proposed in this paper. Firstly, real-time calculation of phase differences at different positions of the beam is achieved through heterodyne coherent array detection and dual high-precision phase-locked loops. Then, a model correlating wave front phase difference with relative angular displacement is established, phase noise during beam transmission and detection processes is analyzed, and algorithm for detecting angular displacement in coherent systems is studied. Finally, a laser communication link is constructed under laboratory condition, and experimental validation work is carried out. When the relative angle deviation is 1°, the phase difference changes by 0.089049795 rad, and the angular displacement detection error of 0.66697μrad(σ). When the relative angle error is 0.603873μrad(σ), the detection sensitivity is −43.93dBm. The experimental results show that in the coherent system, the relative angular displacement detection with high precision can be realized by using the wavefront phase difference of beam, which can support the laser communication tracking system to achieve higher precision beam tracking.

Light-weight neural network for intra-voxel structure analysis.

We present a novel neural network-based method for analyzing intra-voxel structures, addressing critical challenges in diffusion-weighted MRI analysis for brain connectivity and development studies. The network architecture, called the Local Neighborhood Neural Network, is designed to use the spatial correlations of neighboring voxels for an enhanced inference while reducing parameter overhead. Our model exploits these relationships to improve the analysis of complex structures and noisy data environments. We adopt a self-supervised approach to address the lack of ground truth data, generating signals of voxel neighborhoods to integrate the training set. This eliminates the need for manual annotations and facilitates training under realistic conditions. Comparative analyses show that our method outperforms the constrained spherical deconvolution (CSD) method in quantitative and qualitative validations. Using phantom images that mimic in vivo data, our approach improves angular error, volume fraction estimation accuracy, and success rate. Furthermore, a qualitative comparison of the results in actual data shows a better spatial consistency of the proposed method in areas of real brain images. This approach demonstrates enhanced intra-voxel structure analysis capabilities and holds promise for broader application in various imaging scenarios.

Determination of five-parameter grain boundary characteristics in nanocrystalline Ni-W by scanning precession electron diffraction tomography

Determining the full five-parameter grain boundary characteristics from experiments is essential for understanding grain boundaries impact on material properties, improving related models, and designing advanced alloys. However, achieving this is generally challenging, in particular at nanoscale, due to their 3D nature. In our study, we successfully determined the grain boundary characteristics of an annealed nickel-tungsten alloy (NiW) nanocrystalline needle-shaped specimen (tip) containing twins using Scanning Precession Electron Diffraction (SPED) Tomography. The presence of annealing twins in this face-centered cubic (fcc) material gives rise to common reflections in the SPED diffraction patterns, which challenges the reconstruction of orientation-specific virtual dark field (VDF) images required for tomographic reconstruction of the 3D grain shapes. To address this, an automated post-processing step identifies and deselects these shared reflections prior to the reconstruction of the VDF images. Combined with appropriate intensity normalization and projection alignment procedures, this approach enables high-fidelity 3D reconstruction of the individual grains contained in the needle-shaped sample volume. To probe the accuracy of the resulting boundary characteristics, the twin boundary surface normal directions were extracted from the 3D voxelated grain boundary map using a 3D Hough transform. For the sub-set of coherent Σ3 boundaries, the expected {111} grain boundary plane normals were obtained with an angular error of <3° for boundary sizes down to 400 nm². This work advances our ability to precisely characterize and understand the complex grain boundaries that govern material properties.

Analysis of models of measurement and correction of volumetric error of three-axis metal-cutting machine tool

The paper considers the improvement of the quality of products of machined production in connection with the quality of machining of various products and, accordingly, with the accuracy of the equipment used. It is noted that geometrical errors, which account for up to 40 % of the total error of a multi-axis, especially three-axis, metal-cutting machine tool, have the greatest influence on the accuracy of product machining. In order to improve the quality of product machining, it is necessary to correct its parameters according to the measurement information received during machine tool operation, for which the methods of mathematical modelling are used. Models of the volumetric error of a three-coordinate metal-cutting machine tool are developed, taking into account the summands of the first (linear) and second (quadratic) order of smallness. A comparative analysis of the developed models is carried out. The results of experiments on measurement of volumetric errors of the STAN S500 complex and their correction on the basis of the nonlinear theoretical model are given. It is found that in the range of angular errors 0–2.5′ the consideration of quadratic terms of the model in addition to linear ones does not lead to a significant reduction of the volumetric error. It is shown that when processing measurement information of multi-axis metal-cutting machines it is sufficient to limit the consideration of components of the volumetric error not higher than the first order of smallness. The research results are useful for the acceptance and periodic control of the volumetric error of metal-cutting machines, as well as for the programme reduction of the volumetric error.

Experimentally induced pain increases absolute but not relative errors and reduces variability in joint repositioning of the knee joint in healthy participants

BackgroundJoint position sense (JPS) plays an important role in knee joint function. Despite the possible influence of pain on the proprioceptive system, the effects of experimental muscle pain on knee JPS have not been studied. ObjectivesTo investigate if experimentally induced muscle pain affects knee JPS in healthy participants. MethodsMeasurements of knee JPS were conducted before and after the injection of 5.8% sterile hypertonic saline in the vastus medialis muscle of 26 healthy physically active adults. Knee JPS was assessed through a passive/active repositioning paradigm in target angles of 15°, 45° and 60° using an isokinetic dynamometer. Absolute and relative angular errors were calculated. The coefficient of variation analysis was used to assess differences in the angles’ variability during the repositioning task. ResultsAbsolute angular error increased in all three angles following experimentally induced pain. The difference was statistically significant at 45° (p = 0.003, d = 0.6) and 15° (p = 0.047, d = 0.4) but not at 60° (p = 0.064, d = 0.4). Relative error did not show directional bias at 45° (p = 0.272, d = 0.2), 15° (p = 0.483, d = 0.1) or 60° (p = 0.091, d = 0.3). The coefficient of variation analysis revealed a statistically significant reduction in variability at angles of 60° (p = 0.002, d = 0.7) and 15° (p = 0.031, d = 0.4) after the pain intervention. ConclusionThe presence of experimentally induced muscle pain affects the ability of healthy participants to accurately reposition the knee at two angles of knee flexion and reduces movement variability during the repositioning task. Further research is required to determine if these deficits also impact patients with clinical knee pain.