Improved Smart Pseudoscopic-to-Orthoscopic Conversion Algorithm for Integral Imaging With Pixel Information Averaging

The smart pseudoscopic-to-orthoscopic conversion (SPOC) algorithm can synthesize a new elemental image array (EIA) using the already captured EIA, but the algorithm only relies on one simulated ray to establish the mapping relationship between the display pixels and the synthetic pixels. This paper improves the SPOC algorithm and proposes the average SPOC algorithm, which fully considers the converging effect of the synthetic lens on the ray. In the average SPOC algorithm, the simulated rays start from the synthetic pixel, pass through the upper and lower edges of the corresponding synthetic lens, and intersect the display lenses, respectively. Then, the value of the synthetic pixel is equivalent to the average value of display pixels, which correspond to the display lenses covered by the rays. Theoretical analysis points out that the average SPOC algorithm can effectively alleviate the matching error between the display pixels and the synthetic pixels, thereby improving the accuracy of the synthetic elemental image array (SEIA) and the reconstruction effect. According to the experimental results we get, the superiority of the average SPOC algorithm is verified.

Neural Correlates of Knee Extension and Flexion Force Control: A Kinetically-Instrumented Neuroimaging Study

Background: The regulation of muscle force is a vital aspect of sensorimotor control, requiring intricate neural processes. While neural activity associated with upper extremity force control has been documented, extrapolation to lower extremity force control is limited. Knowledge of how the brain regulates force control for knee extension and flexion may provide insights as to how pathology or intervention impacts central control of movement.Objectives: To develop and implement a neuroimaging-compatible force control paradigm for knee extension and flexion.Methods: A magnetic resonance imaging (MRI) safe load cell was used in a customized apparatus to quantify force (N) during neuroimaging (Philips Achieva 3T). Visual biofeedback and a target sinusoidal wave that fluctuated between 0 and 5 N was provided via an MRI-safe virtual reality display. Fifteen right leg dominant female participants (age = 20.3 ± 1.2 years, height = 1.6 ± 0.10 m, weight = 64.8 ± 6.4 kg) completed a knee extension and flexion force matching paradigm during neuroimaging. The force-matching error was calculated based on the difference between the visual target and actual performance. Brain activation patterns were calculated and associated with force-matching error and the difference between quadriceps and hamstring force-matching tasks were evaluated with a mixed-effects model (z > 3.1, p < 0.05, cluster corrected).Results: Knee extension and flexion force-matching tasks increased BOLD signal among cerebellar, sensorimotor, and visual-processing regions. Increased knee extension force-matching error was associated with greater right frontal cortex and left parietal cortex activity and reduced left lingual gyrus activity. Increased knee flexion force-matching error was associated with reduced left frontal and right parietal region activity. Knee flexion force control increased bilateral premotor, secondary somatosensory, and right anterior temporal activity relative to knee extension. The force-matching error was not statistically different between tasks.Conclusion: Lower extremity force control results in unique activation strategies depending on if engaging knee extension or flexion, with knee flexion requiring increased neural activity (BOLD signal) for the same level of force and no difference in relative error. These fMRI compatible force control paradigms allow precise behavioral quantification of motor performance concurrent with brain activity for lower extremity sensorimotor function and may serve as a method for future research to investigate how pathologies affect lower extremity neuromuscular function.

Low-Cost Calibration of Matching Error between Lidar and Motor for a Rotating 2D Lidar

For a rotating 2D lidar, the inaccurate matching between the 2D lidar and the motor is an important error resource of the 3D point cloud, where the error is shown both in shape and attitude. Existing methods need to measure the angle position of the motor shaft in real time to synchronize the 2D lidar data and the motor shaft angle. However, the sensor used for measurement is usually expensive, which can increase the cost. Therefore, we propose a low-cost method to calibrate the matching error between the 2D lidar and the motor, without using an angular sensor. First, the sequence between the motor and the 2D lidar is optimized to eliminate the shape error of the 3D point cloud. Next, we eliminate the attitude error with uncertainty of the 3D point cloud by installing a triangular plate on the prototype. Finally, the Levenberg–Marquardt method is used to calibrate the installation error of the triangular plate. Experiments verified that the accuracy of our method can meet the requirements of the 3D mapping of indoor autonomous mobile robots. While we use a 2D lidar Hokuyo UST-10LX with an accuracy of ±40 mm in our prototype, we can limit the mapping error within ±50 mm when the distance is no more than 2.2996 m for a 1 s scan (mode 1), and we can limit the mapping error within ±50 mm at the measuring range 10 m for a 16 s scan (mode 7). Our method can reduce the cost while the accuracy is ensured, which can make a rotating 2D lidar cheaper.

Spelling Errors and Shouting Capitalization Lead to Additive Penalties to Trustworthiness of Online Health Information: Randomized Experiment With Laypersons

Background The written format and literacy competence of screen-based texts can interfere with the perceived trustworthiness of health information in online forums, independent of the semantic content. Unlike in professional content, the format in unmoderated forums can regularly hint at incivility, perceived as deliberate rudeness or casual disregard toward the reader, for example, through spelling errors and unnecessary emphatic capitalization of whole words (online shouting). Objective This study aimed to quantify the comparative effects of spelling errors and inappropriate capitalization on ratings of trustworthiness independently of lay insight and to determine whether these changes act synergistically or additively on the ratings. Methods In web-based experiments, 301 UK-recruited participants rated 36 randomized short stimulus excerpts (in the format of information from an unmoderated health forum about multiple sclerosis) for trustworthiness using a semantic differential slider. A total of 9 control excerpts were compared with matching error-containing excerpts. Each matching error-containing excerpt included 5 instances of misspelling, or 5 instances of inappropriate capitalization (shouting), or a combination of 5 misspelling plus 5 inappropriate capitalization errors. Data were analyzed in a linear mixed effects model. Results The mean trustworthiness ratings of the control excerpts ranged from 32.59 to 62.31 (rating scale 0-100). Compared with the control excerpts, excerpts containing only misspellings were rated as being 8.86 points less trustworthy, those containing inappropriate capitalization were rated as 6.41 points less trustworthy, and those containing the combination of misspelling and capitalization were rated as 14.33 points less trustworthy (P<.001 for all). Misspelling and inappropriate capitalization show an additive effect. Conclusions Distinct indicators of incivility independently and additively penalize the perceived trustworthiness of online text independently of lay insight, eliciting a medium effect size.

4294 Patient Matching Errors and Associated Safety Events

OBJECTIVES/GOALS: Errors in patient matching could result in serious adverse safety events. Unlike publicized mix-ups by healthcare providers these errors are insidious and with increased data sharing, this is a growing concern in healthcare. The following project will examine patient matching errors and quantify their association with safety. METHODS/STUDY POPULATION: EHR systems perform matching out-of-the-box with unknown quality. Using matching processes outside the EMR, the rate at which matching errors are present was quantified and the erroneous records were flagged providing both comparative measures and data necessary to evaluate patient safety. To understand the relationship between matching and safety we will establish a percent of voluntarily reported safety events in our institution where a matching error existed during an encounter. Any safety events occurring for a flagged patient will be reviewed to determine if matching errors contributed to the safety problem. Not all safety events are reported so we will perform full chart review of a filtered list of medical records that have a higher likelihood of safety events. RESULTS/ANTICIPATED RESULTS: We were able to quantify matching errors, and the preliminary matching error rate is approximately 1%, representing over 700 patients. The work is in progress and we are beginning to determine the association between safety events and incorrect matching. Together these results will provide an incentive to identify errors, make corrections, and develop methods to achieve these objectives. The number of matching errors impacts patient care as well as business operations and is likely to have a negative financial impact on institutions with high error rates regardless of its relationship to safety. DISCUSSION/SIGNIFICANCE OF IMPACT: Patient matching is bundled with EHR software and institutions have little control over error rates, yet bear the liability for resulting clinical error. Institutions need to be able to identify undetected matching errors and any associated safety events and this project will provide that solution.

Spelling Errors and Shouting Capitalization Lead to Additive Penalties to Trustworthiness of Online Health Information: Randomized Experiment With Laypersons (Preprint)

BACKGROUND The written format and literacy competence of screen-based texts can interfere with the perceived trustworthiness of health information in online forums, independent of the semantic content. Unlike in professional content, the format in unmoderated forums can regularly hint at incivility, perceived as deliberate rudeness or casual disregard toward the reader, for example, through spelling errors and unnecessary emphatic capitalization of whole words (online <i>shouting</i>). OBJECTIVE This study aimed to quantify the comparative effects of spelling errors and inappropriate capitalization on ratings of trustworthiness independently of lay insight and to determine whether these changes act synergistically or additively on the ratings. METHODS In web-based experiments, 301 UK-recruited participants rated 36 randomized short stimulus excerpts (in the format of information from an unmoderated health forum about multiple sclerosis) for trustworthiness using a semantic differential slider. A total of 9 control excerpts were compared with matching error-containing excerpts. Each matching error-containing excerpt included 5 instances of misspelling, or 5 instances of inappropriate capitalization (<i>shouting</i>), or a combination of 5 misspelling plus 5 inappropriate capitalization errors. Data were analyzed in a linear mixed effects model. RESULTS The mean trustworthiness ratings of the control excerpts ranged from 32.59 to 62.31 (rating scale 0-100). Compared with the control excerpts, excerpts containing only misspellings were rated as being 8.86 points less trustworthy, those containing inappropriate capitalization were rated as 6.41 points less trustworthy, and those containing the combination of misspelling and capitalization were rated as 14.33 points less trustworthy (<i>P</i>&lt;.001 for all). Misspelling and inappropriate capitalization show an additive effect. CONCLUSIONS Distinct indicators of incivility independently and additively penalize the perceived trustworthiness of online text independently of lay insight, eliciting a medium effect size.