307 resultados para Elbow Joint Position Error
em Queensland University of Technology - ePrints Archive
Resumo:
The purpose of this study was to determine the effects of cryotherapy, in the form of cold water immersion, on knee joint position sense. Fourteen healthy volunteers, with no previous knee injury or pre-existing clinical condition, participated in this randomized cross-over trial. The intervention consisted of a 30-min immersion, to the level of the umbilicus, in either cold (14 ± 1°C) or tepid water(28 ± 1°C). Approximately one week later, in a randomized fashion, the volunteers completed the remaining immersion. Active ipsilateral limb repositioning sense of the right knee was measured, using weight-bearing and non-weight bearing assessments, employing video-recorded 3D motion analysis. These assessments were conducted immediately before and after a cold and tepid water immersion. No significant differences were found between treatments for the absolute (P = 0.29), relative (P = 0.21) or variable error (P = 0.86). The average effect size of the outcome measures was modest (range –0.49 to 0.9) and all the associated 95% confidence intervals for these effect sizes crossed zero. These results indicate that there is no evidence of an enhanced risk of injury, following a return to sporting activity, after cold water.
Resumo:
Objective: To (1) search the English-language literature for original research addressing the effect of cryotherapy on joint position sense (JPS) and (2) make recommendations regarding how soon healthy athletes can safely return to participation after cryotherapy. Data Sources: We performed an exhaustive search for original research using the AMED, CINAHL, MEDLINE, and SportDiscus databases from 1973 to 2009 to gather information on cryotherapy and JPS. Key words used were cryotherapy and proprioception, cryotherapy and joint position sense, cryotherapy, and proprioception. Study Selection: The inclusion criteria were (1) the literature was written in English, (2) participants were human, (3) an outcome measure included JPS, (4) participants were healthy, and (5) participants were tested immediately after a cryotherapy application to a joint. Data Extraction: The means and SDs of the JPS outcome measures were extracted and used to estimate the effect size (Cohen d) and associated 95% confidence intervals for comparisons of JPS before and after a cryotherapy treatment. The numbers, ages, and sexes of participants in all 7 selected studies were also extracted. Data Synthesis: The JPS was assessed in 3 joints: ankle (n 5 2), knee (n 5 3), and shoulder (n 5 2). The average effect size for the 7 included studies was modest, with effect sizes ranging from 20.08 to 1.17, with a positive number representing an increase in JPS error. The average methodologic score of the included studies was 5.4/10 (range, 5–6) on the Physiotherapy Evidence Database scale. Conclusions: Limited and equivocal evidence is available to address the effect of cryotherapy on proprioception in the form of JPS. Until further evidence is provided, clinicians should be cautious when returning individuals to tasks requiring components of proprioceptive input immediately after a cryotherapy treatment.
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Traditional approaches to joint control required accurate modelling of the system dynamic of the plant in question. Fuzzy Associative Memory (FAM) control schemes allow adequate control without a model of the system to be controlled. This paper presents a FAM based joint controller implemented on a humanoid robot. An empirically tuned PI velocity control loop is augmented with this feed forward FAM, with considerable reduction in joint position error achieved online and with minimal additional computational overhead.
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We have taken a new method of calibrating portal images of IMRT beams and used this to measure patient set-up accuracy and delivery errors, such as leaf errors and segment intensity errors during treatment. A calibration technique was used to remove the intensity modulations from the images leaving equivalent open field images that show patient anatomy that can be used for verification of the patient position. The images of the treatment beam can also be used to verify the delivery of the beam in terms of multileaf collimator leaf position and dosimetric errors. A series of controlled experiments delivering an IMRT anterior beam to the head and neck of a humanoid phantom were undertaken. A 2mm translation in the position of the phantom could be detected. With intentional introduction of delivery errors into the beam this method allowed us to detect leaf positioning errors of 2mm and variation in monitor units of 1%. The method was then applied to the case of a patient who received IMRT treatment to the larynx and cervical nodes. The anterior IMRT beam was imaged during four fractions and the images calibrated and investigated for the characteristic signs of patient position error and delivery error that were shown in the control experiments. No significant errors were seen. The method of imaging the IMRT beam and calibrating the images to remove the intensity modulations can be a useful tool in verifying both the patient position and the delivery of the beam.
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This paper presents a vision-based method of vehicle localisation that has been developed and tested on a large forklift type robotic vehicle which operates in a mainly outdoor industrial setting. The localiser uses a sparse 3D edgemap of the environment and a particle filter to estimate the pose of the vehicle. The vehicle operates in dynamic and non-uniform outdoor lighting conditions, an issue that is addressed by using knowledge of the scene to intelligently adjust the camera exposure and hence improve the quality of the information in the image. Results from the industrial vehicle are shown and compared to another laser-based localiser which acts as a ground truth. An improved likelihood metric, using peredge calculation, is presented and has shown to be 40% more accurate in estimating rotation. Visual localization results from the vehicle driving an arbitrary 1.5km path during a bright sunny period show an average position error of 0.44m and rotation error of 0.62deg.
Resumo:
The purpose of this study was to investigate the effects of whole-body cryotherapy (WBC) on proprioceptive function, muscle force recovery following eccentric muscle contractions and tympanic temperature (TTY). Thirty-six subjects were randomly assigned to a group receiving two 3-min treatments of −110 ± 3 °C or 15 ± 3 °C. Knee joint position sense (JPS), maximal voluntary isometric contraction (MVIC) of the knee extensors, force proprioception and TTY were recorded before, immediately after the exposure and again 15 min later. A convenience sample of 18 subjects also underwent an eccentric exercise protocol on their contralateral left leg 24 h before exposure. MVIC (left knee), peak power output (PPO) during a repeated sprint on a cycle ergometer and muscles soreness were measured pre-, 24, 48 and 72 h post-treatment. WBC reduced TTY, by 0.3 °C, when compared with the control group (P<0.001). However, JPS, MVIC or force proprioception was not affected. Similarly, WBC did not effect MVIC, PPO or muscle soreness following eccentric exercise. WBC, administered 24 h after eccentric exercise, is ineffective in alleviating muscle soreness or enhancing muscle force recovery. The results of this study also indicate no increased risk of proprioceptive-related injury following WBC.
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Learning Outcome: Gain knowledge in the area of dietetic training in Australia and the benefits of collaborative partnerships between government and universities to achieve improvements in dietetic service delivery, evidenced based practice, and student placements. Prisoners have high rates of chronic disease, however dietetic services and research in this sector is limited. Securing high quality professional practice placements for dietetic training in Australia is competitive, and prisons provide exciting opportunities. Queensland University of Technology (QUT) has a unique twenty year partnership with Queensland Corrective Services (QCS) with a service learning model placing final year dietetic students within prisons. Building on this partnership, in 2007 a new joint position was funded to establish dietetic services to over 5500 prisoners and support viable best practice dietetic education. Evaluation of the past three years of this partnership has shown an expansion of QUT student placements in Queensland prisons, with a third of final year students each undertaking 120 hours of foodservice management practicum. Student evaluations of placement over this period are much higher than the University average. Through the joint position student projects have been targeted on strategic areas to support nutrition and dietetic policy and practice. Projects have been broadened from menu reviews to more comprehensive quality improvement and dietetic research activities, with all student learning activities transferrable to other foodservice settings. Student practice in the prisons has been extended beyond foodservice management to include group education and dietetic counseling. For QCS, student placements have equated to close to a full-time dietitian position, with nutrition policy now being implemented as an outcome of this support. This innovative partnership has achieved a sustainable student placement model, supported research, whilst delivering dietetic services to a difficult to access group. Funding Disclosure: None
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The use of GNSS tracked Lagrangian drifters allows more realistic quantification of fluid motion and dispersion coefficients than Eulerian techniques because such drifters are analogues of particles that are relevant to flow field characterisation and pollutant dispersion. Using the fast growing Real Time Kinematic (RTK) positioning technique derived from Global Satellite Navigation Systems (GNSS), drifters are developed for high frequency (10 Hz) sampling with position estimates to centimetre accuracy. The drifters are designed with small size and less direct wind drag to follow the sub-surface flow which characterizes dispersion in shallow waters. An analysis of position error from stationary observation indicates that the drifter can efficiently resolve motion up to 1 Hz. The result of the field deployments of the drifter in conjunction with acoustic Eulerian devices shows higher estimate of the drifter streamwise velocities. Single particle statistical analysis of field deployments in a shallow estuarine zone yielded dispersion coefficients estimate comparable to those of dye tracer studies. The drifters capture the tidal elevation during field studies in a tidal estuary.
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Introduction Markerless motion capture systems are relatively new devices that can significantly speed up capturing full body motion. A precision of the assessment of the finger’s position with this type of equipment was evaluated at 17.30 ± 9.56 mm when compare to an active marker system [1]. The Microsoft Kinect was proposed to standardized and enhanced clinical evaluation of patients with hemiplegic cerebral palsy [2]. Markerless motion capture systems have the potential to be used in a clinical setting for movement analysis, as well as for large cohort research. However, the precision of such system needs to be characterized. Global objectives • To assess the precision within the recording field of the markerless motion capture system Openstage 2 (Organic Motion, NY). • To compare the markerless motion capture system with an optoelectric motion capture system with active markers. Specific objectives • To assess the noise of a static body at 13 different location within the recording field of the markerless motion capture system. • To assess the smallest oscillation detected by the markerless motion capture system. • To assess the difference between both systems regarding the body joint angle measurement. Methods Equipment • OpenStage® 2 (Organic Motion, NY) o Markerless motion capture system o 16 video cameras (acquisition rate : 60Hz) o Recording zone : 4m * 5m * 2.4m (depth * width * height) o Provide position and angle of 23 different body segments • VisualeyezTM VZ4000 (PhoeniX Technologies Incorporated, BC) o Optoelectric motion capture system with active markers o 4 trackers system (total of 12 cameras) o Accuracy : 0.5~0.7mm Protocol & Analysis • Static noise: o Motion recording of an humanoid mannequin was done in 13 different locations o RMSE was calculated for each segment in each location • Smallest oscillation detected: o Small oscillations were induced to the humanoid mannequin and motion was recorded until it stopped. o Correlation between the displacement of the head recorded by both systems was measured. A corresponding magnitude was also measured. • Body joints angle: o Body motion was recorded simultaneously with both systems (left side only). o 6 participants (3 females; 32.7 ± 9.4 years old) • Tasks: Walk, Squat, Shoulder flexion & abduction, Elbow flexion, Wrist extension, Pronation / supination (not in results), Head flexion & rotation (not in results), Leg rotation (not in results), Trunk rotation (not in results) o Several body joint angles were measured with both systems. o RMSE was calculated between signals of both systems. Results Conclusion Results show that the Organic Motion markerless system has the potential to be used for assessment of clinical motor symptoms or motor performances However, the following points should be considered: • Precision of the Openstage system varied within the recording field. • Precision is not constant between limb segments. • The error seems to be higher close to the range of motion extremities.
Error, Bias, and Long-Branch Attraction in Data for Two Chloroplast Photosystem Genes in Seed Plants
Resumo:
Sequences of two chloroplast photosystem genes, psaA and psbB, together comprising about 3,500 bp, were obtained for all five major groups of extant seed plants and several outgroups among other vascular plants. Strongly supported, but significantly conflicting, phylogenetic signals were obtained in parsimony analyses from partitions of the data into first and second codon positions versus third positions. In the former, both genes agreed on a monophyletic gymnosperms, with Gnetales closely related to certain conifers. In the latter, Gnetales are inferred to be the sister group of all other seed plants, with gymnosperms paraphyletic. None of the data supported the modern ‘‘anthophyte hypothesis,’’ which places Gnetales as the sister group of flowering plants. A series of simulation studies were undertaken to examine the error rate for parsimony inference. Three kinds of errors were examined: random error, systematic bias (both properties of finite data sets), and statistical inconsistency owing to long-branch attraction (an asymptotic property). Parsimony reconstructions were extremely biased for third-position data for psbB. Regardless of the true underlying tree, a tree in which Gnetales are sister to all other seed plants was likely to be reconstructed for these data. None of the combinations of genes or partitions permits the anthophyte tree to be reconstructed with high probability. Simulations of progressively larger data sets indicate the existence of long-branch attraction (statistical inconsistency) for third-position psbB data if either the anthophyte tree or the gymnosperm tree is correct. This is also true for the anthophyte tree using either psaA third positions or psbB first and second positions. A factor contributing to bias and inconsistency is extremely short branches at the base of the seed plant radiation, coupled with extremely high rates in Gnetales and nonseed plant outgroups. M. J. Sanderson,* M. F. Wojciechowski,*† J.-M. Hu,* T. Sher Khan,* and S. G. Brady
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This paper presents the preliminary results in establishing a strategy for predicting Zenith Tropospheric Delay (ZTD) and relative ZTD (rZTD) between Continuous Operating Reference Stations (CORS) in near real-time. It is anticipated that the predicted ZTD or rZTD can assist the network-based Real-Time Kinematic (RTK) performance over long inter-station distances, ultimately, enabling a cost effective method of delivering precise positioning services to sparsely populated regional areas, such as Queensland. This research firstly investigates two ZTD solutions: 1) the post-processed IGS ZTD solution and 2) the near Real-Time ZTD solution. The near Real-Time solution is obtained through the GNSS processing software package (Bernese) that has been deployed for this project. The predictability of the near Real-Time Bernese solution is analyzed and compared to the post-processed IGS solution where it acts as the benchmark solution. The predictability analyses were conducted with various prediction time of 15, 30, 45, and 60 minutes to determine the error with respect to timeliness. The predictability of ZTD and relative ZTD is determined (or characterized) by using the previously estimated ZTD as the predicted ZTD of current epoch. This research has shown that both the ZTD and relative ZTD predicted errors are random in nature; the STD grows from a few millimeters to sub-centimeters while the predicted delay interval ranges from 15 to 60 minutes. Additionally, the RZTD predictability shows very little dependency on the length of tested baselines of up to 1000 kilometers. Finally, the comparison of near Real-Time Bernese solution with IGS solution has shown a slight degradation in the prediction accuracy. The less accurate NRT solution has an STD error of 1cm within the delay of 50 minutes. However, some larger errors of up to 10cm are observed.
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This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.
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The joints of a humanoid robot experience disturbances of markedly different magnitudes during the course of a walking gait. Consequently, simple feedback control techniques poorly track desired joint trajectories. This paper explores the addition of a control system inspired by the architecture of the cerebellum to improve system response. This system learns to compensate the changes in load that occur during a cycle of motion. The joint compensation scheme, called Trajectory Error Learning, augments the existing feedback control loop on a humanoid robot. The results from tests on the GuRoo platform show an improvement in system response for the system when augmented with the cerebellar compensator.
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In this paper, we present a method for the recovery of position and absolute attitude (including pitch, roll and yaw) using a novel fusion of monocular Visual Odometry and GPS measurements in a similar manner to a classic loosely-coupled GPS/INS error state navigation filter. The proposed filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. An observability analysis of the proposed filter is performed, showing that the scale factor, position and attitude errors are fully observable under acceleration that is non-parallel to velocity vector in the navigation frame. The observability properties of the proposed filter are demonstrated using numerical simulations. We conclude the article with an implementation of the proposed filter using real flight data collected from a Cessna 172 equipped with a downwards-looking camera and GPS, showing the feasibility of the algorithm in real-world conditions.
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In this paper we explore the ability of a recent model-based learning technique Receding Horizon Locally Weighted Regression (RH-LWR) useful for learning temporally dependent systems. In particular this paper investigates the application of RH-LWR to learn control of Multiple-input Multiple-output robot systems. RH-LWR is demonstrated through learning joint velocity and position control of a three Degree of Freedom (DoF) rigid body robot.