Position Accuracy Research Articles

A New Versatile Tool for Accurate Bracket Positioning—An In Vitro Study

Aim To evaluate and compare the accuracy of bracket positioning in the incisogingival and mesiodistal aspects with the MBT gauge and new multipurpose bracket positioning tool. Materials and Methods Bracket positioning of maxillary anterior teeth ( n=30) was assessed on the typhodont model. The UNC-15 (University of North Carolina) probe was modified as an MBP tool. Five different malocclusions: (a) Class II Division 1 ( n=6); (b) Class II Division 2 ( n=6); (c) Class I with mesially inclined maxillary anterior teeth ( n=6); (d) Class I with crowding in maxillary anterior teeth-3 mm ( n=6); (e) Class I with different vertical heights of maxillary anterior teeth ( n=6). The measurements of the study were divided into three groups; Group A: Central Incisor, Group B: Lateral Incisor, and Group Canine, based on positioning with MBT Gauge and MBP tool. The measurements on each tooth were recorded using vernier calliper, on the basis of which the discrepancy in vertical and axial bracket positioning was assessed. Results The comparative evaluation of the MBT gauge and MBP Tool showed statistically insignificant differences between all the groups (p>0.05). The mean standard deviation with the MBT gauge was 0.5-0.7 mm, whereas with the MBP tool was only 0.05- 0.3 mm only; suggesting clinical relevance and acuity during bracket positioning. Conclusion The MBP tool is relatively accurate and comparable to the MBT gauge as the horizontal and vertical arm of the MBP tool facilitates proper visualization by coinciding with the long axis of the tooth on the typhodont model leading to augmented precision.

Clinical evaluation of autonomous robotic-assisted full-arch implant surgery: A 1-year prospective clinical study.

This prospective clinical study aimed to evaluate the accuracy and 1-year clinical follow-up performance of dental implant placement with an autonomous dental implant robot (ADIR) system in full-arch implant surgery. Twelve patients with edentulous arches or final dentition received 102 implants using the ADIR system. Global platform deviation, global apex deviation, and global angular deviation between the planned and actual implants were calculated after surgery. Data were statistically analyzed for factors including jaws, implant positions, patient sequences, implant systems, and implant length. Surgery duration was recorded. Patients were followed for 3 months and 1 year after surgery. Periodontal parameters, buccal bone thickness (BBT), and facial vertical bone wall peak (IP-FC) were recorded. Among the 102 implants, the mean (SD) global platform deviation, global apex deviation, and global angular deviation were 0.53 (0.19) mm, 0.58 (0.17) mm, and 1.83 (0.82)°, respectively. The deviation differences between the mandible and maxilla did not show statistical significance (p > .05). No statistically significant differences were found for the jaws, implant positions, patient sequences, implant systems, and implant length to the deviations (p > .05). The periodontal parameters, the BBT, and IP-FC remained stable during 1-year follow-up. The ADIR system showed excellent positional accuracy. The 1-year follow-up after full-arch implant surgery indicated that the ADIR system could achieve promising clinical performance. Additional clinical evidence is requisite to furnish guidelines for the implementation of the ADIR system in full-arch implant surgery.

Mixed-reality improves execution of templated glenoid component positioning in shoulder arthroplasty: a CT imaging analysis

Glenoid placement is critical for successful outcomes in total shoulder arthroplasty (TSA). Preoperative templating with three-dimensional imaging has improved implant positioning, but deviations from the planned inclination and version still occur. Mixed-Reality (MR) is a novel technology that allows surgeons intra-operative access to three-dimensional imaging and templates, capable of overlaying the surgical field to help guide component positioning. The purpose of this study was to compare the execution of preoperative templates using MR vs.standard instruments (SIs). Retrospective review of 97 total shoulder arthroplasties (18 anatomic, 79 reverse) from a single high-volume shoulder surgeon between January 2021 and February 2023, including only primary diagnoses of osteoarthritis, rotator cuff arthropathy, or a massive irreparable rotator cuff tear. To be included, patients needed a templated preoperative plan and then a postoperative computed tomography scan. Allocation to MR vs. SI was based on availability of the MR headset, industry technical personnel, and the templated preoperative plan loaded into the software, but preoperative or intraoperative patient factors did not contribute to the allocation decision. Postoperative inclination and version were measured by two independent, blinded physicians and compared to the preoperative template. From these measurements, we calculated the mean difference, standard deviation (SD), and variance to compare MR and SI. Comparing 25MR to 72 SI cases, MR significantly improved both inclination (P<.001) and version (P<.001). Specifically, MR improved the mean difference from preoperative templates (by 1.9° inclination, 2.4° version), narrowed the SD (by 1.7° inclination, 1.8° version), and decreased the variance (11.7-3.0 inclination, 14.9-4.3 version). A scatterplot of the data demonstrates a concentration of MR cases within 5° of plan relative to SI cases typically within 10° of plan. There was no difference in operative time. MR improved the accuracy and precision of glenoid positioning. Although it is unlikely that 2° makes a detectable clinical difference, our results demonstrate the potential ability for technology like MR to narrow the bell curve and decrease the outliers in glenoid placement. This will be particularly relevant as MR and other similar technologies continue to evolve into more effective methods in guiding surgical execution.

Relationship between GIX, SIDX, and ROTI ionospheric indices and GNSS precise positioning results under geomagnetic storms

Ionospheric indices give information about ionospheric perturbations, which may cause absorption, diffraction, refraction, and scattering of radio signals, including those from global navigation satellite systems (GNSS). Therefore, there may be a relationship between index values and GNSS positioning results. A thorough understanding of ionospheric indices and their relationship to positioning results can help monitor and forecast the reliability and accuracy of GNSS positioning and support the precision and safety of life applications. In this study, we present the relationship between three indices: Gradient Ionosphere indeX (GIX), Sudden Ionospheric Disturbance indeX (SIDX), and Rate of Total electron content Index (ROTI) in relation to precise positioning results. We used two approaches: precise point positioning (PPP) and relative positioning for long baselines. We focus on GNSS stations located in Europe for two selected geomagnetic storms: March 17, 2015, and May 22, 2015. Our results show that in the case of PPP, positioning degradation occurred mainly at high latitudes and was mostly caused by rapid small-scale changes in ionospheric electron content represented by SIDX and ROTI. We also showed a significant correlation between cycle slips of GNSS signals and ROTI (0.88). The most significant degradations for relative positioning for low and medium latitudes were associated with large spatial gradients reflected by the GIX.

An Integrated Model Based Prediction of Machining Accuracy for Milling Machine

The accuracy of machining can be predicted during the design process of CNC machine tools, while the prediction accuracy depends on the prediction model. However, when establishing the prediction model, the coupling effect among the machine tool’s different components is always ignored for modeling efficiency, so this will lead to its reliability cannot be guaranteed. To address this problem, the model reduction theory and the lumped parameter method are used in this study to set the state-space equations of the essential structural parts. Moreover, the electro-mechanical coupling parameter equation of the servo system is transformed into a state-space equation. Then the state-space equations of the components and the servo system are coupled to establish the machine tool dynamic model. Furthermore, a theoretical model of instantaneous undeformed chip thickness is found, and according to the linear relationship between the micro-cutting force and the instantaneous undeformed chip thickness, the instantaneous cutting force model of the cylindrical milling cutter is established. Based on these, the integrated model, which considers the mechanical structure, control system and cutting force, is obtained and further used in Simulink to build the machining accuracy prediction platform, as well as the accuracy of the integrated prediction model is verified. Moreover, the prediction model established by the integrated modeling method can effectively simulate the actual machining conditions of the machine tool, and the superiority of prediction is confirmed by comparing the simulated and measured results in peripheral milling applications. The results show the error in the system response efficiency is 14.8%, while the error in position accuracy and delay characteristics is less than 10%, the error between the predicted size of the prediction model and the actual size is within 28 μm, a minimum prediction error is 7 μm.

A Literature Review on Stewart–Gough Platform Calibrations

Abstract Researchers have studied Stewart–Gough platforms, also known as Gough–Stewart platforms or hexapod platforms extensively for their inherent fine control characteristics. Their studies led to the potential deployment opportunities of Stewart–Gough platforms in many critical applications such as medical field, engineering machines, space research, electronic chip manufacturing, automobile manufacturing, etc. Some of these applications need micro- and nano-level movement control in 3D space for the motions to be precise, complicated, and repeatable; a Stewart–Gough platform fulfills these challenges smartly. For this, the platform must be more accurate than the specified application accuracy level and thus proper calibration for a parallel robot is crucial. Forward kinematics-based calibration for these hexapod machines becomes unnecessarily complex and inverse kinematics complete this task with much ease. To experiment with different calibration techniques, various calibration approaches were implemented by using external instruments, constraining one or more motions of the system, and using extra sensors for auto or self-calibration. This survey paid attention to those key methodologies, their outcome, and important details related to inverse kinematic-based parallel robot calibrations. It was observed during this study that the researchers focused on improving the accuracy of the platform position and orientation considering the errors contributed by one source or multiple sources. The error sources considered are mainly kinematic and structural, in some cases, environmental factors also are reviewed; however, those calibrations are done under no-load conditions. This study aims to review the present state of the art in this field and highlight the processes and errors considered for the calibration of Stewart–Gough platforms.

Clinical Outcome Analysis of Robot-Assisted Pedicle Screw Insertion in the Treatment of Ankylosing Spondylitis Complicated with Spinal Fractures

BackgroundVague spinal anatomical landmarks in patients with ankylosing spondylitis (AS) make intraoperative insertion of pedicle screws difficult under direct vision. Currently, the clinical outcome is significantly improved with robot guidance. This study aims to explore the efficacy of robot-assisted pedicle screw insertion in treating AS combined with spinal fractures. Methods40 patients (341 screws) who underwent pedicle screw insertion with AS complicated with spinal fractures were included. According to different surgical methods, 16 patients (135 screws) were classified into the robot group and 24 (206 screws) into the free-hand group. Intraoperative blood loss, operative duration, and adverse events were compared between the two groups. Gertzbein and Robbins classification was used to classify the accuracy of screw position. Clinical outcomes were evaluated by Visual Analog Scale, Japanese Orthopedic Association, and Oswestry Disability Index. ResultsNo statistically significant differences between baseline data of the groups. The difference in the blood loss between groups wasn’t significant, nor was the operative duration. No severe adverse events related to pedicle screw insertion were reported in either group. Notably, the accuracy of screw insertion was significantly higher in the robot group (129/135) than in the free-hand group (182/206). The lateral perforation prevalence didn’t differ among groups. VAS in the third month postoperatively was lower in the robot group than in the free-hand group, with a significant difference. ConclusionsThe study demonstrates statistically superior accuracy and surgical outcome of robot-assisted pedicle screw insertion in the treatment of AS complicated with spinal fractures compared with the traditional free-hand operation.

Omnidirectional Sensor Design for Distributed Laser Measurement Systems

Distributed laser measurement systems, widely used in high-end equipment such as airplanes, ships, and other manufacturing fields, face challenges in large spatial measurements due to laser plane obstructions and weak intersections. This paper introduces a novel omnidirectional sensor with enhanced adaptability to complex environments and improved measurement accuracy. Initially, an integrated omnidirectional measurement model is established, followed by the analysis of the optical path of the front-end detector, and the design of a signal-conditioning circuit for the photoelectric conversion of the front-end laser signal, Subsequently, a circuit testing platform is established to validate the detection functionality, and the corresponding results indicate that the symmetry of the output waveform is under 10 ns, the response time is under 100 ns, and the maximum detection distance is 22 m. Further, experimental results demonstrate the superiority of omnidirectional sensors over planar ones in complex environments, successfully receiving 360° laser signals. The positional accuracy of the common point to be measured on the top of the omnidirectional sensor is confirmed to exceed 0.05 mm, and the accuracy of the angle of attitude exceeds 0.04°. Using the laser tracker, the measurement accuracy of the system is verified to be better than 0.3 mm. When rotating in the horizontal and pitch directions, the measurement accuracy is better than 0.35 mm and 0.47 mm, respectively, fulfilling the sub-millimeter precision requirement and expanding the application scope of distributed laser measurement systems.

VaDAR: Varstrometry for Dual AGN Using Radio Interferometry

Binary and dual active galactic nuclei (AGNs) are an important observational tool for studying the formation and dynamical evolution of galaxies and supermassive black holes. An entirely new method for identifying possible AGN pairs makes use of the exquisite positional accuracy of Gaia to detect astrometrically variable quasars, in tandem with the high spatial resolution of the Karl G. Jansky Very Large Array (VLA). We present a new pilot study of radio observations of 18 quasars (0.8 ≤ z ≤ 2.9), selected from the Sloan Digital Sky Survey DR16Q and matched with the Gaia DR3. All 18 targets are identified by their excess astrometric noise in Gaia. We targeted these 18 quasars with the VLA at 2–4 GHz (S band) and 8–12 GHz (X band), providing resolutions of 0.″65 and 0.″2, respectively, in order to constrain the origin of this variability. We combine these data with ancillary radio survey data and perform radio spectral modeling. The new observations are used to constrain the driver of the excess astrometric noise. We find that ∼44% of the target sample is likely to be either candidate dual AGN or gravitationally lensed quasars. Ultimately, we use this new strategy to help identify and understand this sample of astrometrically variable quasars, demonstrating the potential of this method for systematically identifying kiloparsec-scale dual quasars.

Assessment Accuracy of Standard Point Positioning Enhanced by Observation and Position Domain Filtering Utilizing a Multi-Epoch Least-Squares Integration Method

To enhance the positioning accuracy of standalone GNSS receivers in environments unable to provide precise ephemeris and clock offset, such as undeveloped forest areas that lack network communication and power supply, this study employed the Time Difference Carrier Phase (TDCP) technology to improve the positioning accuracy of Standard Point Positioning (SPP), where the Least-Squares (LS) and the extended Multi-Epoch Least Squares (MELS) method were applied in the position domain filtering for a single GNSS receiver and compare its performance with the existing observation domain filtering method. Firstly, the simulated data sets with various positioning accuracies were used to verify the effectiveness and convergence of the LS filtering methods. The results indicate that the LS filtering method produces a lower root mean square (RMS) error than the original strategy. Secondly, this study uses two kinematic GNSS data sets to evaluate the performance of the observation and position domain filtering, with an emphasis on the MELS method. The numerical experiment results show that the position domain LS filtering method outperforms the other two methods. The open environment experiments result shows that the positioning domain filtering method achieved positioning accuracies of 0.202 m, 0.843 m, and 2.036 m in the E, N, and U directions, respectively, with improvements of 68.0%, 21.6%, and 24.0%, compared to the original algorithm which achieved positioning accuracies of 0.631 m, 1.076 m, and 2.680 m. It also achieved improvements of 24.0%, 4.0%, and 18.3%, respectively, compared to the observation domain filtering method with positioning accuracies of 0.353 m, 0.886 m, and 2.526 m. The forest scenes experiments result shows that the positioning domain filtering method achieved positioning accuracies of 1.308 m, 1.375 m, and 2.133 m in the E, N, and U directions, respectively, with improvements of 42.4%, 36.2%, and 27.6%, compared to original algorithm which achieved positioning accuracies of 1.863 m, 1.873 m, and 2.722 m, and also achieved improvements of 27.0%, 19.4% and 10.6%, respectively, comparing to observation domain filtering method with positioning accuracies of 1.661 m, 1.642 m and 2.359 m. Moreover, the examination of the LS method results based on different epochs reveals that the filtering accuracy increases as more epochs are incorporated into the position domain integration and the enhancement value reaches a few millimeters.

The influence of the da Vinci surgical robot on electromagnetic tracking in a clinical environment

Robot-assisted surgery is increasingly used in surgery for cancer. Reduced overview and loss of anatomical orientation are challenges that might be solved with image-guided surgical navigation using electromagnetic tracking (EMT). However, the robot’s presence may distort the electromagnetic field, affecting EMT accuracy. The aim of this study was to evaluate the robot’s influence on EMT accuracy. For this purpose, two different electromagnetic field generators were used inside a clinical surgical environment: a table top field generator (TTFG) and a planar field generator (PFG). The position and orientation of sensors within the electromagnetic field were measured using an accurate in-house developed 3D board. Baseline accuracy was measured without the robot, followed by stepwise introduction of potential distortion sources (robot and robotic instruments). The absolute accuracy was determined within the entire 3D board and in the clinical working volume. For the baseline setup, median errors in the entire tracking volume within the 3D board were 0.9 mm and 0.3° (TTFG), and 1.1 mm and 0.4° (PFG). Adding the robot and instruments did not affect the TTFG’s position accuracy (p = 0.60), while the PFG’s accuracies decreased to 1.5 mm and 0.7° (p < 0.001). For both field generators, when adding robot and instruments, accuracies inside the clinical working volume were higher compared to the entire tracking 3D board volume, 0.7 mm and 0.3° (TTFG), and 1.1 mm and 0.7° (PFG). Introduction of a surgical robot and robotic instruments shows limited distortion of the EMT field, allowing sufficient accuracy for surgical navigation in robotic procedures.

Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry

Using a novel methodology that integrates incremental dynamic analysis (IDA) and unmanned aerial vehicle positioning (POS) analysis, this study aims to assess the seismic risk of brick structures in rural China. This method can collect a lot of data and accurately anticipate seismic damage by combining UAV oblique photography with IDA analysis. Because rural China has many masonry structures, the project will design unique seismic risk mitigation strategies. High-resolution cameras on Unmanned Aerial Vehicles capture realistic photographs of rural brick buildings. The collected data is carefully examined to reveal architectural and structural elements. The project uses dynamic post-processing software from the CHC Geomatics Office to improve UAV-reference station position accuracy. This program analyzes UAV POS data disparities. The findings allow rural Chinese brick buildings to be assessed for seismic sensitivity during unexpected ground shaking occurrences. UAV tilt-photography reduces manpower and expenditures, improving inquiry efficiency. This combination improves seismic risk response. The IDA and UAV POS analysis are essential for earthquake preparedness and risk mitigation. This data-driven method informs lawmakers, urban planners, and disaster management authorities worldwide, improving earthquake engineering and catastrophe resilience programs. This work improves seismic threat assessment and masonry structure fortification, making earthquake-prone buildings safer. Thus, rural communities benefit from it.

Position Tracking Control of 4-DOF Underwater Robot Leg Using Deep Learning

This paper presents a novel hybrid control method for position tracking of an underwater quadruped walking robot. The proposed approach combines an existing position-tracking control method with a deep-learning neural network. The neural network compensates for non-linear dynamic characteristics, such as the effect of fluid, without relying on mathematical modeling. To achieve this, a Multi-Layer Perceptron neural network is designed to analyze joint torque in relation to the joint angle and angular velocity of the robot, as well as the position and orientation of the foot tip and environmental data. The improvement in tracking control performance is evaluated using a 4-DOF underwater robot leg. For the neural network design, position tracking control data, including dynamic characteristics, were collected through position command-based position tracking control. Afterward, a learning model was constructed and trained to predict joint torque related to the robot’s motion and posture. This learning process incorporates non-linear dynamic characteristics, such as joint friction and the influence of fluid, in the joint torque prediction. The proposed method is then combined with conventional task-space PD control to perform position-tracking control with enhanced performance. Finally, the proposed method is evaluated using the underwater robot leg and compared to a single task-space PD controller. The proposed method demonstrates higher position accuracy with similar joint torque output, thereby increasing compliance and tracking performance simultaneously.

Application of a long short-term memory neural network algorithm fused with Kalman filter in UWB indoor positioning

Ultra-wideband technology has good anti-interference capabilities and development prospects in indoor positioning. Since ultra-wideband will be affected by random errors in indoor positioning, to exploit the advantages of the Kalman filter (KF) and the long short-term memory (LSTM) network, this paper proposes a long short-term memory neural network algorithm fused with the Kalman filter (KF–LSTM) to improve UWB positioning. First, the ultra-wideband data is processed through KF to weaken the noise in the data, and then the data is fed into the LSTM network for training, and the capability of the LSTM network to process time series features is employed to obtain more accurate label positions. Finally, simulation and measurement results show that the KF–LSTM algorithm achieves 71.31%, 37.28%, and 49.31% higher average positioning accuracy than the back propagation (BP) network, (back propagation network fused with the Kalman filter (KF-BP), and LSTM network algorithms, respectively, and the KF–LSTM algorithm performs more stably. Meanwhile, the more noise the data contains, the more obvious the stability contrast between the four algorithms.

Tree Diameter at Breast Height (DBH) Estimation Using an iPad Pro LiDAR Scanner: A Case Study in Boreal Forests, Ontario, Canada

The aim of this study was to determine whether the iPad Pro 12th generation LiDAR sensor is useful to measure tree diameter at breast height (DBH) in natural boreal forests. This is a follow-up to a previous study that was conducted in a research forest and identified the optimal method for (DBH) estimation as a circular scanning and fitting ellipses to 4 cm stem cross-sections at breast height. The iPad Pro LiDAR scanner was used to acquire point clouds for 15 sites representing a range of natural boreal forest conditions in Ontario, Canada, and estimate DBH. The secondary objective was to determine if tested stand (species composition, age, density, understory) or tree (species, DBH) factors affected the accuracy of estimated DBH. Overall, estimated DBH values were within 1 cm of actual DBH values for 78 of 133 measured trees (59%). An RMSE of 1.5 cm (8.6%) was achieved. Stand age had a large effect (&gt;0.15) on the accuracy of estimated DBH values, while density, understory, and DBH had moderate effects (0.05–0.14). No trend was identified between accuracy and stand age. Accuracy improved as understory density decreased and as tree DBH increased. Inertial measurement unit (IMU) and positional accuracy errors with the iPad Pro scanner limit the feasibility of using this device for forest inventories.

MPG-LSD: A high-quality line segment detector based on multi-scale perceptual grouping

Existing methods that rely on a single Gaussian scale to detect line segments could yield poor line continuity and inferior orientation and position accuracy due to insufficient suppression of quantization noise inherent in digital images. To address this fundamental issue, a novel multi-scale perceptual grouping-based line segment detector (MPG-LSD) is proposed in this paper. Our multi-scale perceptual grouping is developed to identify and aggregate collinear pixels that have similar gradient orientations for producing line segment candidates, not only over the input image but also across a set of Gaussian scales. Multi-scale line segment refinement and validation are then further developed and implemented to produce the final detection result, which delivers high quality in terms of line continuity, orientation and position accuracy. To enrich the evaluation of line segment detection performance, a new dataset consisting of high-resolution and natural noise-corrupted images with line segment annotations is constructed. Extensive experimental results show that our proposed MPG-LSD can outperform the current state-of-the-arts by a large margin.

Topological optimization design for support structure under multiple loading conditions

In view of the lightweight and high stiffness requirements of a certain type of spacecraft support, combined with the special performance and environment of the support, topology optimization technology is introduced into the optimal design of the support structure in the space field. The topology optimization and design of the support are carried out with the stiffness as the objective function and the quality as the constraint condition, and the design of "space hugging configuration" is proposed, and the simulation verification and experimental verification are carried out. Firstly, different load conditions of the support were analyzed and studied. Secondly, the initial model was established based on the relative position relationship between the support and the mounting surface of the loaded equipment. Finally, a design method of the support structure was established based on the combination of topology optimization under multi-load conditions and size optimization considering the influence of strength. The stiffness and strength of the optimized structure were checked under multiple load conditions, and the fundamental frequency was 2.05 times of the index requirement. The maximum response stress is lower than the yield limit of the material used, which meets the strength requirement. Finally, the vibration test is carried out to verify the support. After the test is completed, the position accuracy of the support interface meets the requirements of the index. The obtained bracket has high structural stability, meets the high performance requirements of the load equipment, verifies the feasibility of the topology optimization method, and provides an effective method for the design of lightweight high-stiffness structures.

Mako versus ROSA: comparing surgical accuracy in robotic total knee arthroplasty.

There is increasing adoption of robotic surgical technology in Total Knee Arthroplasty. The ROSA® knee system can be used in either image-based mode (using pre-operative calibrated radiographs) or imageless modes (using intra-operative bony registration). The Mako knee system is an image-based system (using a pre-operative CT scan). This study aimed to compare surgical accuracy between the ROSA and Mako systems with specific reference to joint line height, patella height, posterior condylar offset and tibial slope. This was a retrospective review of a prospectively collected data of the initial 50 consecutive ROSA TKAs and the initial 50 consecutive Mako TKAs performed by two high-volume surgeons. To determine the accuracy of component positioning, the immediate post-operative radiograph was reviewed and compared with the immediate pre-operative radiograph with regards to joint line height (JLH), patella height (PH), tibial slope (TS) and posterior condylar offset (PCO). Mean difference between pre- and post-operative radiographs using the ROSA knee system of joint line height was 0.47mm (SD 0.95) posterior condylar offset 0.16mm (SD 0.76), tibial slope 0.9 degrees (SD 1.6) and patella height 0.01 (SD 0.05). Mean difference using the MAKO knee system of joint line height was 0.26 (SD 1.08), posterior condylar offset -0.26mm (SD 0.78), tibial slope 1.8 degrees and patella height 0.03. No significant difference was demonstrated between the accuracy of component positioning of the ROSA or MAKO knee systems. Our study is the first study to compare the accuracy of the ROSA and MAKO knee systems in total knee arthroplasty. Both systems are highly accurate in restoring native posterior condylar offset, joint line height, tibial slope and patella height in TKA with no significant difference demonstrated between the two groups.

Effectiveness and safety of robot-assisted minimally invasive transforaminal lumbar interbody fusion for degenerative lumbar spinal diseases: a systematic review and meta-analysis.

Robot-assisted (RA) technology has been widely used in spine surgery. This analysis aimed to compare the effectiveness and safety of RA minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) and fluoroscopy-assisted (FA) MIS-TLIF for degenerative lumbar spinal diseases (DLSD). PubMed, Web of Science, Cochrane Library, and China National Knowledge Infrastructure were systematically searched, and the outcomes included surgical parameters [operation time, blood loss, number of fluoroscopic, accuracy of pedicle screw position, superior facet joint violation (FJV)], and clinical indexes (Visual Analog Scale (VAS), Oswestry Disability Index (ODI), Japanese Orthopaedic Association (JOA) score, clinical efficacy, hospital stays, complications). Eleven articles involving 1066 patients were included. RA group produced better results than the FA group in operation time (WMD = -6.59; 95% CI -12.79 to -0.40; P = 0.04), blood loss (WMD = -34.81; 95% CI -50.55 to -19.08; P < 0.0001), number of fluoroscopic (WMD = -18.24; 95% CI -30.63 to -5.85; P = 0.004), accuracy of pedicle screw position: Grade A (OR = 3.16; 95% CI 2.36-4.23; P < 0.00001), Grade B (OR = 0.39; 95% CI 0.28-0.54; P < 0.00001), Grade C (OR = 0.27; 95% CI 0.13-0.54; P = 0.0002), and Grade D (OR = 0.17; 95% CI 0.03-0.98; P = 0.05), FJV: Grade 0 (OR = 3.27; 95% CI 1.34-8.02; P = 0.010), Grade 1 (OR = 0.24; 95% CI 0.16-0.38; P < 0.00001), Grade 2 (OR = 0.24; 95% CI 0.12-0.51; P = 0.0002), and Grade 3 (OR = 0.26; 95% CI 0.07-0.93; P = 0.04). But no significant differences in VAS score, ODI, JOA score, clinical efficacy, hospital stays, and complications. These results demonstrate a significant improvement in the intraoperative course of the RA technique. However, RA-MIS-TLIF has not yet demonstrated significant advantages in terms of postoperative symptom relief and functional improvement. Future research and clinical practice should further explore the efficacy of this technique to optimize outcomes and quality of life for patients with DLSD. The study was registered in the PROSPERO (CRD42023454405).

On the Evaluation of Diverse Vision Systems towards Detecting Human Pose in Collaborative Robot Applications.

Tracking human operators working in the vicinity of collaborative robots can improve the design of safety architecture, ergonomics, and the execution of assembly tasks in a human-robot collaboration scenario. Three commercial spatial computation kits were used along with their Software Development Kits that provide various real-time functionalities to track human poses. The paper explored the possibility of combining the capabilities of different hardware systems and software frameworks that may lead to better performance and accuracy in detecting the human pose in collaborative robotic applications. This study assessed their performance in two different human poses at six depth levels, comparing the raw data and noise-reducing filtered data. In addition, a laser measurement device was employed as a ground truth indicator, together with the average Root Mean Square Error as an error metric. The obtained results were analysed and compared in terms of positional accuracy and repeatability, indicating the dependence of the sensors' performance on the tracking distance. A Kalman-based filter was applied to fuse the human skeleton data and then to reconstruct the operator's poses considering their performance in different distance zones. The results indicated that at a distance less than 3 m, Microsoft Azure Kinect demonstrated better tracking performance, followed by Intel RealSense D455 and Stereolabs ZED2, while at ranges higher than 3 m, ZED2 had superior tracking performance.