Movement Accuracy Research Articles

The NanoSIMS-HR: The Next Generation of High Spatial Resolution Dynamic SIMS.

The high lateral resolution and sensitivity of the NanoSIMS 50 and 50L series of dynamic SIMS instruments have enabled numerous scientific advances over the past 25 years. Here, we report on the NanoSIMS-HR, the first major upgrade to the series, and analytical tests in a suite of sample types, including an aluminum sample containing silicon crystals, microalgae, and plant roots colonized with a symbiotic fungus. Significant improvements have been made in the Cs+ ion source, high voltage (HV) control, stage reproducibility, and other aspects of the instrument that affect performance. The modified design of the NanoSIMS-HR thermal-ionization Cs+ source enables a 5 pA primary ion beam to be focused into a 100 nm spot, a ∼2.5-fold increase compared to Cs+ sources on previous instruments (∼2 pA at 100 nm). The brightness of the new Cs+ source enables an ultimate lateral resolution as high as 30 nm and improved detection limits for a given analysis area. Sample stage movement accuracy is higher than 500 nm, enabling many-fold higher throughput automated analyses. With the new HV control, the primary ion beam impact energy can be reduced from 16 to 2 keV, which enables higher depth resolution during depth profiling (a 2-fold improvement), albeit with a 5-fold decrease in lateral resolution. In the NanoSIMS-HR, the secondary ion column and detection system are identical to those used in the previous series, and the isotopic analysis performance is as precise as in previous NanoSIMS instruments.

Research on the promotion effect of personalized training program based on biomechanics on the physical health of college students

Biomechanics-based personalized training programs can significantly improve physical health among college students, but there is limited evidence on how these programs affect spinal twist stretch function and overall health, despite previous research demonstrating the potential benefits of such programs. In this study, the influence of a biomechanics-based personalized training program investigates the physical health of a college student population. This study involved 68 college students, divided into two groups: 34 participants undergoing a personalized biomechanics-based training program (Group A) and 34 participants following a standard exercise regimen (Group B). The training program included exercises designed to enhance spinal twist stretch activation and stability. The participants’ core muscle activation was recorded through EMG from rhomboids, latissimus dorsi, and external obliques, while kinematic data were obtained from a three-dimensional motion analysis system. The assessments were done pre and post-8-week structured nutrition and physical activity modification period. These data are stimulated using SPSS, to compare pre and post-test measurements within each group and to determine the differences between spinal twist stretch and global physical health gains using paired t-tests, analyze of variance (ANOVA) descriptive statistics, and correlation analysis. The result demonstrated that Group A significantly improved spinal twists, stretch, and physical health among college students. Exercises targeting specific biomechanical principles exhibited more pronounced spinal twist stretch activation. The program improved trunk stability and movement accuracy, with a moderate correlation between muscle activation and overall physical health improvements. This approach improved core stability and muscle function but also led to better overall health outcomes compared to standard exercise regimens.

An in vivo three-dimensional, kinematics study of the cervical vertebrae under physiological loads in patients with cervical spondylosis

Background ContextStudies of in vivo kinematic differences between healthy individuals and those with cervical spondylosis (CS) have been reported, but only movements under non-physiological loads have been investigated. Differences in the in vivo, cervical kinematics between healthy individuals and those with CS are unknown. PurposeTo investigate the in vivo, cervical kinematics of patients with CS under physiological loads. Study DesignThis was a retrospective, case-controlled study that used three-dimensional (3D) to 3D registration techniques combined with conical beam computed tomography (CBCT) to investigate the cervical kinematics of patients with CS. Patient SampleTwenty individuals diagnosed with CS were selected for study participation and matched with 20 participants who did not have CS and were in good health. Outcome MeasuresPfirrmann grading,intervertebral range of motion(ROM), kinematics and cross-sectional area of posterior neck muscles(CAPNM). MethodsAll study participants underwent seven CBCT scans of their cervical vertebrae. The 3D segmental motion features of the vertebra in vivo were calculated using 3D-to-3D volume registration to overlay images of the vertebra at each functional position. The 3D range of motion (ROM) of each cervical segment was expressed with six degrees of freedom using Euler angles and translated onto a coordinate system. A kinematic subgroup analysis was conducted based on the severity of symptoms within the CS group, and differences in muscle volume between the CS and control groups were also evaluated. Project supported by the National Natural Science Foundation of China (Grant No. 81960408,82260445), Training plan for academic and technical leaders of major disciplines in Jiangxi Province(Grant No.20204BCJL22047), Clinical Cultivation Project of The First Affiliated Hospital of Nanchang University (Grant No.YFYLCYJPY 20220203).The authors declare no conflict of interest in preparing this article. ResultsThe CS group exhibited noticeable reductions in the primary rotational ROMs of left-right rotation at C4-C5, C5-C6, C6-C7, C4-C7, and C1-C7 compared to the controls. During left-right bending, there were no significant differences in the primary ROMs, coupled translations, or rotations between the two groups. However, compared to controls, the CS group had significantly lower primary ROMs for C4 C7, C1-C7 and C5-C6 during flexion-extension. During left-right rotation, the primary rotations and coupled lateral bending at C6-C7 were significantly increased in the mild CS group compared to the moderate CS group. In the mild CS group, the primary ROM of the C4-C5 and C5-C6 during flexion-extension was significantly greater than that of the moderate CS group. ConclusionsFor the first time, the in vivo 3D kinematics of the cervical spine during head movement under physiological load in CS individuals have been adequately described and compared with healthy cervical vertebrae, which can be used as a reference point for future studies. The application of CBCT helps to obtain accurate and precise movement information of CS patients and effectively enhance the evaluation results obtained from imaging information.

A radiation therapy platform to enable upright cone beam computed tomography and future upright treatment on existing photon therapy machines

AbstractBackgroundThe conventional lying down position for radiation therapy can be challenging for patients due to pain, swallowing or breathing issues. To provide an alternative upright treatment position for these patients, we have developed a portable rotating radiation therapy platform which integrates with conventional photon treatment machines. The device enables cone‐beam computed tomography (CBCT) imaging of patients in an upright position, and the future delivery of therapeutic radiation.PurposeTo design, manufacture, and test a device for upright radiation therapy. A collaborative partnership between physicists, engineers, radiation therapists, radiation oncologists, implementation researchers and consumers was established, to create a device that meets both the clinical and technical requirements of upright radiation therapy. The device is central to a clinical trial (ACTRN12623000498695) which will evaluate upright image quality in the context of future image guided radiation therapy for patients with lung cancer or head and neck cancer.MethodsThe weight and physical constraints of the device were assessed with respect to the American civilian population. The final design was evaluated with a series of tests to characterize the angular accuracy of the platform rotation and the reproducibility of the platform setup position in a radiation treatment room. To acquire an upright CBCT, the platform movement system was synchronized to the kilo‐voltage fluoroscopic imaging on an existing treatment machine. The accuracy of the synchronization was evaluated by assessing the positional reproducibility of upright CBCT imaging of a chest phantom.ResultsThe platform has a weight limit of up to 125 kg which is suitable for approximately 90% of males and 95% of females. The platform has physical constraints that accommodate approximately 95.6% of males and 99.6% of females: a maximum seated height of 97.5 cm, a maximum hip breadth of 63.0 cm, and maximum elbow to knuckle length of 46.5 cm. The angular accuracy of the motion system is within ±0.15° over a full rotation, which is within the guidelines for machine movement accuracy in radiation therapy (1 mm/1°). The platform is a portable device and can be reproducibly positioned in a radiation therapy treatment room with a translational range within ±0.04 mm and a rotational range within ±0.025°. The CBCT imaging can reproducibly detect the position of a chest phantom with a translational uncertainty of ±0.07 mm and a rotational uncertainly of ±0.22°, when imaging is acquired following a strict procedure.ConclusionThe upright radiation therapy platform is suitable for the evaluation of CBCT imaging in the context of image guided radiation therapy. The platform will allow the investigation of open questions in upright radiation therapy in the areas of patient experience, positional stability, anatomical changes, and treatment delivery. Improvements to the materials in the radiation beam line, synchronization with the existing treatment machine, and increasing the device weight limit are suggested prior to delivery of future upright treatments.

Passive shoulder occupational exoskeleton reduces shoulder muscle coactivation in repetitive arm movements

Humans naturally employ muscle coactivation to facilitate a broad range of movements, enhancing joint stability and movement accuracy. However, excessive muscle coactivation can become unfavorable or even detrimental. This phenomenon is often observed in industrial workers who endure repetitive or prolonged joint stress, particularly in areas such as the shoulders. Prolonged stress can result in soft tissue damage and the onset of work-related musculoskeletal disorders (MSDs). In recent years, there have been efforts to mitigate the emergence of work-related MSDs among industrial workers through the implementation of upper-limb occupational exoskeletons (OEs). While previous research has demonstrated their effectiveness in reducing shoulder muscle activation, particularly in static and overhead work activities, there has been a lack of studies examining the impact of upper-limb OEs on muscle coactivation during repetitive arm movements. To bridge this gap in knowledge, our study systematically assesses the influence of a passive exoskeleton’s anti-gravitational support on shoulder muscle coactivation during repetitive arm movements. Results show that peak and mean coactivation levels linearly decrease with the increase of the amount of anti-gravitational support provided by the upper-limb OE, reaching approximately 51% and 54%, respectively. Conversely, the percentage of the movement cycle corresponding to the coactivation peak appears unaffected by the level of assistance. This study marks the first instance in which a passive upper-limb OE has been shown to reduce shoulder muscle coactivations, potentially paving the way for a novel methodology in their evaluation.

Precision Orthodontic Force Simulation Using Nodal Displacement-Based Archwire Loading Approach.

Precision in force simulationis critical for forecasting tooth movement and optimizing orthodontic treatment strategies. While traditional techniques have provided valuable insights, there remains a need for improved methodologies that can seamlessly integrate with fixed orthodontic practices. This study aims to refine orthodontic force simulation techniques by integrating a nodal displacement approach within finite element analysis, specifically designed to enhance prediction accuracy in tooth movement and optimize orthodontic treatment planning. Three-dimensional patient-specific models of the Tooth, Periodontal Ligament, and Bone Complex (TPBC) of five volunteers were created, along with models of brackets and wires. The simulation involved an initial step of estimating node displacements to align the archwire with the brackets, followed by a subsequent step to attain the required tooth movement and determine the orthodontic force. Experimental validation of the simulation results was performed using an orthodontic force tester (OFT). Utilizing the nodal displacement approach, the simulation successfully positioned the archwire onto the brackets. When benchmarked against the OFT, 80% of the simulated force directions exhibited angular discrepancies of less than 5°. Additionally, the absolute differences in force magnitude reached 20.06 cN, and in moments, up to 71.76 cN mm. The relative differences were as high as 9.55% for force and 13.83% for moments. These findings represent an improvement of up to 10.45% in force accuracy and 8.87% in moment accuracy compared to median values reported in most recent literature. In this research, a nodal displacement methodology was employed to simulate orthodontic forces with precision across the dental arch. The results demonstrate the approache's potential to enhance the accuracy of force prediction in orthodontic treatment planning, thereby advancing our understanding of orthodontic biomechanics.

Age-stratified assessment of orthodontic tooth movement outcomes with clear aligners

ObjectiveThis study compared the achieved tooth movement to that predicted in the preliminary simulated digital treatment plan between adults and teenagers.Materials and methodsRecords of 60 patients (30 adults; mean age: 36.6 ± 11.36 years, and 30 teenagers; mean age: 16.23 ± 2.25 years) were randomly selected. Initial and predicted models were obtained from the initial simulated treatment plan. The first model of the refinement scan was labeled as achieved. SlicerCMF software (version 3.1; https://www.slicer.org) was used to superimpose the achieved and predicted digital models over the initial ones with regional superimposition on relatively stable first molars. 600 teeth were measured in each group for horizontal, vertical, angular movements, and transverse dimensions. Accuracy was defined as the achieved amount of movement minus predicted and was calculated for each individual and compared between teens and adults.ResultsThe mandibular inter-canine width accuracy was statistically significant between groups (p = 0.050). Significant under-correction in horizontal movements was noted for mandibular first premolars in teenagers compared to adults (p = 0.037). There was considerable over-correction in horizontal movements for mandibular central and lateral incisors between groups (p < 0.05). No significant difference was observed between groups in the vertical plane. Rotations were underachieved for maxillary first premolars, more in adults than teenagers (p = 0.017).ConclusionThe accuracy of achieved versus predicted tooth movement between adults and teenagers was significant for the inter-canine width. Mandibular central and lateral incisors showed significantly greater over-correction in adults in the horizontal plane. The accuracy of rotations and vertical movements was comparable.

Development of a Large-Aperture Coordinate Precision Measurement Instrument Using Differential Geometric Error Weighting

The accuracy of traditional measuring machines is affected by the measuring range and sensitive geometric errors, and it is not possible to combine large caliber and high-precision measurements. This study proposes a differential geometric error-weighting method for designing a high-precision, large-diameter measuring machine. The machine utilized a zero-Abbe arm structure and applied the rigid body theory and small-angle hypothesis to model geometric errors. Weights were calculated for 23 geometric errors, identifying eight sensitive ones. A picometer-precision laser interferometer (quDIS) with a theoretical positioning accuracy of 0.2 nm/mm and standard flat rulers are used to ensure highly accurate positioning of the Y-axis/Z-axis of the measuring platform and reduce the straightness of both axes by approximately 75%, with radial and axial runout of the rotary table under 100 nm. The development and design method of the high-precision measuring machine proposed in this study is applicable to large-diameter high-precision flexible measurement, and the accurate control of measuring machine movement accuracy is realized by calculating the geometric error weights.

Lower Limb Motion Recognition Based on sEMG and CNN-TL Fusion Model.

To enhance the classification accuracy of lower limb movements, a fusion recognition model integrating a surface electromyography (sEMG)-based convolutional neural network, transformer encoder, and long short-term memory network (CNN-Transformer-LSTM, CNN-TL) was proposed in this study. By combining these advanced techniques, significant improvements in movement classification were achieved. Firstly, sEMG data were collected from 20 subjects as they performed four distinct gait movements: walking upstairs, walking downstairs, walking on a level surface, and squatting. Subsequently, the gathered sEMG data underwent preprocessing, with features extracted from both the time domain and frequency domain. These features were then used as inputs for the machine learning recognition model. Finally, based on the preprocessed sEMG data, the CNN-TL lower limb action recognition model was constructed. The performance of CNN-TL was then compared with that of the CNN, LSTM, and SVM models. The results demonstrated that the accuracy of the CNN-TL model in lower limb action recognition was 3.76%, 5.92%, and 14.92% higher than that of the CNN-LSTM, CNN, and SVM models, respectively, thereby proving its superior classification performance. An effective scheme for improving lower limb motor function in rehabilitation and assistance devices was thus provided.

Proprioceptive acuity for locating and controlling movements of a hand-held tool

We investigated proprioceptive acuity for location and motion of a never seen hand-held tool (30 cm long rod) and the accuracy of movements to place tool parts in the location of remembered visual targets. Ten blindfolded right-handed subjects (5 females) reached with the tool held in the right hand to touch the tip and midpoint to the stationary and moving left index-tip, to the right and left ear lobes and to remembered visual target locations. We also tested accuracy of left hand rod reaches to the ear lobes to determine if rod dimensions and control of tool movements experienced during right hand tool use could be used to accurately localize the rod parts when held in the left hand. Errors for right hand-held rod-tip movements to touch the stationary and moving left index-tip averaged only about 1 cm larger than observed previously for right hand movements to touch its index-tip to the left index-tip. The tool-tip was localized with lower mean distance errors (about 1 cm) than the tool-midpoint (5.5–6.5 cm) when reaching to touch the ear lobes with the rod in right and left hands. Right hand reaches to place the tool- tip and midpoint in remembered visual target locations were inaccurate with large overshoots of close targets and undershoots of far targets, similar to previous reports for reaching with the right hand to remembered visual targets. These results support the distalization hypothesis, that tool the tool endpoint becomes the effective upper limb endpoint when using the tool.

The Effect of Dry Immersion on the Characteristics of Joystick Control during the Performance of a Visual-Motor Task in Men and Women

A study of the effect of Dry Immersion (DI) on the characteristics of joystick control during a visual-motor task in men and women was conducted. It is shown that in the first days of DI there is a deterioration in the performance of the visual-motor task – an increase in time indicators and a decrease in movement accuracy. By the end of DI, most of the parameters returned to the control level indicating the adaptation of the hand movement control mechanisms to immersion conditions. However, despite the similarity of the effect of DI on changes in the parameters of movement trajectories in men and women, it was shown that both in control and in DI, women performed the presented visual-motor task faster and more accurately due to a longer latency time. In the early days of DI, the characteristics of task performance in women changed less than in men, which indicated a better adaptation of women to the conditions of DI. In the process of adaptation to DI factors, men and women had different strategies for performing visual-motor tasks.

Application of derivative and integral terminal sliding modes in leader-follower type systems"

Subject matter: The study focuses on the control methods for dr20 type robot swarms, specifically on the derivative and integral terminal sliding mode control combined with a nonlinear disturbance observer. The problem of effective swarm control is highly relevant in the current conditions of automation and robotics, especially in the context of performing complex tasks in limited space and in the presence of disturbances. Goal: The development and analysis of a simulation model for the movement of a robot swarm using advanced control methods to ensure system accuracy and stability. The research aims to improve the control methods for robot swarms, enhancing their efficiency and reliability in various operational conditions. Tasks: 1) Develop a simulation model of a robot swarm in the CoppeliaSimEDU environment, considering all necessary parameters for modeling real operating conditions. 2) Implement control algorithms for the leader and followers to maintain the swarm structure and avoid collisions. 3) Conduct a series of experiments to test the effectiveness of the proposed methods, analyzing the results in terms of stability and control accuracy. Methods: Modeling in CoppeliaSimEDU, implementing control algorithms based on derivative and integral terminal sliding mode control, applying a nonlinear disturbance observer to improve system stability. The applied methods allow for the consideration of various disturbances and ensure high control accuracy. Results: he proposed control model allows achieving high following accuracy and collision avoidance even in complex conditions. Experiments have shown that the control methods ensure the stability and accuracy of the robot swarm's movement, reducing the response time to external disturbances. The research results demonstrate that the use of derivative and integral terminal sliding mode control combined with a nonlinear disturbance observer significantly enhances the efficiency of multi-robot systems. Conclusions: The use of advanced control methods significantly improves the efficiency of multi-robot systems, ensuring their reliability and accuracy in real operating conditions. The proposed methods can be applied in various fields where the coordination of a large number of robots is required, including logistics, rescue operations, and environmental monitoring.

Upper and Lower Limb Training Evaluation System Based on Virtual Reality Technology.

Upper and lower limb rehabilitation training is essential for restoring patients' physical movement ability and enhancing muscle strength and coordination. However, traditional rehabilitation training methods have limitations, such as high costs, low patient participation, and lack of real-time feedback. The purpose of this study is to design and implement a rehabilitation training evaluation system based on virtual reality to improve the quality of patients' rehabilitation training. This paper proposes an upper and lower limb rehabilitation training evaluation system based on virtual reality technology, aiming to solve the problems existing in traditional rehabilitation training. The system provides patients with an immersive and interactive rehabilitation training environment through virtual reality technology, aiming to improve patients' participation and rehabilitation effects. This study used Kinect 2.0 and Leap Motion sensors to capture patients' motion data and transmit them to virtual training scenes. The system designed multiple virtual scenes specifically for different upper and lower limbs, with a focus on hand function training. Through these scenes, patients can perform various movement training, and the system will provide real-time feedback based on the accuracy of the patient's movements. The experimental results show that patients using the system show higher participation and better rehabilitation training effects. Compared with patients receiving traditional rehabilitation training, patients using the virtual reality system have significantly improved movement accuracy and training participation. The virtual reality rehabilitation training evaluation system developed in this study improves the quality of patients' rehabilitation and provides personalized treatment information to medical personnel through data collection and analysis, promoting the systematization and personalization of rehabilitation training. This system is innovative and has broad application potential in the field of rehabilitation medicine.

Computer Vision-Driven Movement Annotations to Advance fNIRS Pre-Processing Algorithms.

Functional near-infrared spectroscopy (fNIRS) is beneficial for studying brain activity in naturalistic settings due to its tolerance for movement. However, residual motion artifacts still compromise fNIRS data quality and might lead to spurious results. Although some motion artifact correction algorithms have been proposed in the literature, their development and accurate evaluation have been challenged by the lack of ground truth information. This is because ground truth information is time- and labor-intensive to manually annotate. This work investigates the feasibility and reliability of a deep learning computer vision (CV) approach for automated detection and annotation of head movements from video recordings. Fifteen participants performed controlled head movements across three main rotational axes (head up/down, head left/right, bend left/right) at two speeds (fast and slow), and in different ways (half, complete, repeated movement). Sessions were video recorded and head movement information was obtained using a CV approach. A 1-dimensional UNet model (1D-UNet) that detects head movements from head orientation signals extracted via a pre-trained model (SynergyNet) was implemented. Movements were manually annotated as a ground truth for model evaluation. The model's performance was evaluated using the Jaccard index. The model showed comparable performance between the training and test sets (J train = 0.954; J test = 0.865). Moreover, it demonstrated good and consistent performance at annotating movement across movement axes and speeds. However, performance varied by movement type, with the best results being obtained for repeated (J test = 0.941), followed by complete (J test = 0.872), and then half movements (J test = 0.826). This study suggests that the proposed CV approach provides accurate ground truth movement information. Future research can rely on this CV approach to evaluate and improve fNIRS motion artifact correction algorithms.

Enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic

Visual servoing is a commonly employed approach in robotics and unmanned aerial vehicles (UAVs) that facilitates accurate object positioning and movement control by utilizing visual feedback. As quadrotors gain popularity, more control methods have been developed. This article presents a method for enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic. Unlike traditional visual servoing, which relies on a fixed gain and often encounters challenges with velocity convergence and maintaining the object in the field of view, this method is designed to enhance the visual servo control of quadrotors by dynamically adjusting the gain of the IBVS system through a fuzzy logic controller. This controller adaptively adjusts the servo gain in response to feature errors and the depth of the object's feature points. MATLAB simulations clearly demonstrate the superior performance of this fuzzy logic integrated method compared to classical approaches, showcasing enhanced control capabilities in challenging environments.

Gait compensations, pain, and functional performance during the six minute walk test in individuals with unilateral hip osteoarthritis

BackgroundIndividuals with unilateral hip osteoarthritis walk with kinematic and spatiotemporal compensations compared to healthy individuals. Our purpose was to determine associations between gait, pain, and functional performance during the six-minute walk test. MethodsTrunk and hip kinematics and spatiotemporal gait outcomes were recorded from individuals with unilateral hip osteoarthritis using inertial sensors (Xsens Technologies). Pain was collected prior to and at the end of the six-minute walk test. Paired t-tests were conducted to evaluate gait between limbs and between the first and final minutes of walking. Correlations were conducted between gait, pain, and six-minute walk test performance. FindingsNineteen participants (8 females, age: 63 ± 5 yrs., BMI: 29.0 ± 4.5 kg/m2) completed the study. Between-limb differences in hip flexion, hip extension, and trunk forward flexion peak angles were observed during the six-minute walk test (P < .05). Participants demonstrated an increase in trunk forward flexion of the osteoarthritis side (t = −2.34, P = .031) and a bilateral decrease in stride length (osteoarthritis limb: t = 2.98, P = .008, non- osteoarthritis limb: t = 3.17, P = .006) from the first to the final minute of walking. Greater pain was associated with greater osteoarthritis limb hip extension (first minute: r = −0.506, P = .027, final minute: r = −0.53, P = .020) and greater hip abduction (r = 0.46, P = .046) during the final minute of walking. InterpretationsGait compensations increase throughout the six-minute walk test, and pain associates with hip kinematics during the six-minute walk test. Wearable technology may allow for more accurate clinical movement assessments.

CRTF-MoeICP: A robust coarse-to-fine reflector-based LiDAR indoor positioning algorithm

The reflector-based Light Detection and Ranging (LiDAR) positioning method is susceptible to environmental interferences, resulting in instability. This instability not only reduces movement accuracy but also poses safety hazards. To solve the above problems in the application of LiDAR sensors in the field of indoor positioning, we propose a Coarse Registration algorithm based on the Triangular Feature (CRTF) and a fine registration algorithm based on Multi-level outlier elimination and Iterative Closest Point (MoeICP) for the reflector-based LiDAR positioning. The proposed coarse-to-fine positioning algorithm CRTF-MoeICP addresses the issue of reflector-based LiDAR positioning failure arising from the improper selection of the initial transformation matrix and outlier interference in indoor structured industrial environments. The experiment results show that the CRTF-MoeICP algorithm can ensure the stable registration of the LiDAR point cloud and the reflector map by completely removing all outliers, greatly improving the indoor positioning stability of LiDAR sensors. Besides, the proposed algorithm can be realized by LiDARs with different performance, and improve the static positioning repeatability to ±3 mm. The high precision and stable positioning results improve the motion accuracy, ensuring that the Automatic Guided Vehicle (AGV) can accurately and stably complete the handling task.

Impairments in Proprioceptively-Referenced Limb and Eye Movements in Chronic Stroke.

Upper limb proprioceptive impairments are common after stroke and affect daily function. Recent work has shown that stroke survivors have difficulty using visual information to improve proprioception. It is unclear how eye movements are impacted to guide action of the arm after stroke. Here, we aimed to understand how upper limb proprioceptive impairments impact eye movements in individuals with stroke. Control (N = 20) and stroke participants (N = 20) performed a proprioceptive matching task with upper limb and eye movements. A KINARM exoskeleton with eye tracking was used to assess limb and eye kinematics. The upper limb was passively moved by the robot and participants matched the location with either an arm or eye movement. Accuracy was measured as the difference between passive robot movement location and active limb matching (Hand-End Point Error) or active eye movement matching (Eye-End Point Error). We found that individuals with stroke had significantly larger Hand (2.1×) and Eye-End Point (1.5×) Errors compared to controls. Further, we found that proprioceptive errors of the hand and eye were highly correlated in stroke participants (r = .67, P = .001), a relationship not observed for controls. Eye movement accuracy declined as a function of proprioceptive impairment of the more-affected limb, which was used as a proprioceptive reference. The inability to use proprioceptive information of the arm to coordinate eye movements suggests that disordered proprioception impacts integration of sensory information across different modalities. These results have important implications for how vision is used to actively guide limb movement during rehabilitation.

Fault Tolerant Control in Underwater Vehicles

The article discusses the problem of adaptive system synthesis to provide the detection, estimation, and elimination of the negative consequences of faults in the thrusters of underwater robots and deviations of their parameters. For this purpose, an approach consisting of three stages is proposed. At the first stage, based on a bank of diagnostic observers, deviations of the thruster parameters from their nominal values or the occurrence of errors in the readings of its sensors are detected. At the second stage, the magnitudes of the detected deviations and errors are estimated using sliding mode observers. To estimate not only single but also multiple faults, the additional sliding mode observers are used. At the third stage, a control signal is generated to retain the basic dynamic properties of the thruster based on the estimated magnitudes of deviations and errors. Thus, the main contribution of this paper is designing the systems compensating for the consequences of faults occurring in the thrusters of the UR and errors in the readings of the angular velocity sensors. This avoids reducing the accuracy of movement along specified trajectories, as well as preventing accidents that could lead to the loss of the vehicle. The operability and efficiency of the proposed systems were tested using computer simulations and experimental studies on an electro-mechanical stand.

Evaluating Surgical Accuracy in Bimaxillary Surgery: A Systematic Review and Meta-Analysis of Mandible-First versus Maxilla-First Approaches.

Mandible-first surgery (MdFS) has gained attention as an alternative to the traditional maxilla-first surgery (MxFS) in bimaxillary procedures. Given the distinct sequence of operations between these approaches, evaluating the clinical advantages of MdFS compared to MxFS is crucial for optimizing surgical decision-making. This systematic review and meta-analysis examine intraoperative achievability and postoperative stability between these two surgical approaches. A thorough literature search was performed using PubMed, Embase, Web of Science, and MEDLINE, covering articles published from 2013 to 2023. Studies included were retrospective, prospective, and randomized trials that compared the accuracy and/or stability of MdFS with MxFS. The primary endpoint for the meta-analysis was the standardized mean difference in surgical accuracy for translational movements, with a secondary focus on rotational accuracy. A total of 11 studies encompassing 712 patients met the inclusion criteria. The analysis suggested that MdFS might reduce accuracy in the sagittal dimension (CI, 0.05 to 0.74) but offered greater achievability in the vertical direction (CI, - 0.47 to - 0.07). Additionally, MdFS was associated with a relatively posterior (CI, - 1.18 to - 0.60) and inferior (CI, - 0.64 to - 0.07) positioning of the maxillomandibular complex. Despite certain limitations, our findings indicate that MdFS can achieve clinical outcomes similar to MxFS in terms of both accuracy and stability. However, further researches with larger sample sizes and more rigorous study designs are necessary to validate these conclusions. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of contents or the online Instructions to Authors www.springer.com/00266 .