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Results for “Error minimization”

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At least 469 records · Page 26Linked to original sources

PubMed1999

Interobserver errors in anthropometry.

To present basic information on the interobserver precision and accuracy of 32 selected anthropometric measurement items, six observers measured each of 37 subjects once in two days. The data were analyzed by using ANOVA, and mean absolute bias, standard deviation of bias, and mean absolute bias in standard deviation unit were used as measures of bias. By comparing the results of the two days, the effects of the practice on measurement errors were also investigated. Variance was overestimated by more than 10% in five measurements. Interobserver error variance and random error variance were highly correlated with each other. Measures of the bias were significantly correlated with interobserver and especially with random error variances. The interobserver errors were drastically reduced on the second day in the measurement items in which the causes of the interobserver errors could be specified. It was speculated that even when the definitions of the landmarks and measurement items were clear, the ambiguity in the practical procedures in locating landmarks, applying instruments, and so on, permitted each observer to develop his or her own measurement technique, and it in turn caused interobserver errors. To minimize interobserver and random errors, the standardization of measurement technique should be extended to the details of the practical procedures.

Adult↗

PubMed1994

Reliability of error estimates from the minimal model: implications for measurements in physiological studies.

MINMOD provides an estimate of the error in the insulin sensitivity index (SI) and glucose effectiveness at basal insulin (Sg) as the fractional standard deviation (FSD). The validity of the FSD estimate has not been assessed in a large number of human studies, nor has a comparison of the accuracies achievable using the two different intravenous glucose tolerance test (IVGTT) protocols (glucose only and tolbutamide protocol) been performed. To address these two issues, we obtained the FSD value and performed Monte Carlo simulations for 237 IVGTT studies. The FSD underestimated the true error as determined as the coefficient of variation from Monte Carlo simulation (COV-MC) with the ratio of COV-MC to FSD being 3.07 +/- 0.20 (mean +/- SE) for SI using the tolbutamide protocol. Additionally, the mean COV-MC for glucose-only protocol was approximately two to three times that for the tolbutamide protocol for both SI and Sg. We conclude that FSD underestimates the true error in SI and Sg. Additionally, more accurate results are obtained from the tolbutamide protocol than with the glucose-only protocol.

Computer Simulation↗

PubMed2004

The loss function of sensorimotor learning.

Motor learning can be defined as changing performance so as to optimize some function of the task, such as accuracy. The measure of accuracy that is optimized is called a loss function and specifies how the CNS rates the relative success or cost of a particular movement outcome. Models of pointing in sensorimotor control and learning usually assume a quadratic loss function in which the mean squared error is minimized. Here we develop a technique for measuring the loss associated with errors. Subjects were required to perform a task while we experimentally controlled the skewness of the distribution of errors they experienced. Based on the change in the subjects' average performance, we infer the loss function. We show that people use a loss function in which the cost increases approximately quadratically with error for small errors and significantly less than quadratically for large errors. The system is thus robust to outliers. This suggests that models of sensorimotor control and learning that have assumed minimizing squared error are a good approximation but tend to penalize large errors excessively.

Adaptation, Physiological↗

PubMed1978

Comparative validity of random-interval and fixed-interval urinalysis schedules.

Accurate detection of unprescribed drug use by addicts in treatment may facilitate their rehabilitation. Many clinics collect urine samples at random, using fixed-interval collection schedules, which are not free from sampling error. Random-interval schedules minimize sampling error and consequently increase detectability of drug use by eliminating safe periods during which drug use cannot be detected. We compared these two methods by observing rates of detected opiate- and quinine-positive samples preceding and following implementation of random-interval schedules. Detected drug use doubled initially. As detection and clinical sanctions became more certain, drug use declined to well below its former level. Programs that use fixed-interval schedules may underdetect drug use by more than 50%. If patients can reliably predict safe periods, the possibility of using drugs without fear of detection may impede their rehabilitation.

Appointments and Schedules↗

PubMed1998

In situ measurement of dihedral angles at liquid grain boundary inclusions.

This work describes experimental aspects of the measurement of relative interfacial energies from the equilibrium dihedral angles of small liquid inclusions or precipitates at interfaces in solids using in situ transmission electron microscopy. We demonstrate how limitations such as faceting, free surfaces, and projection errors can be handled to minimize experimental errors.

Alloys↗

PubMed2002

Consistent landmark and intensity-based image registration.

Two new consistent image registration algorithms are presented: one is based on matching corresponding landmarks and the other is based on matching both landmark and intensity information. The consistent landmark and intensity registration algorithm produces good correspondences between images near landmark locations by matching corresponding landmarks and away from landmark locations by matching the image intensities. In contrast to similar unidirectional algorithms, these new consistent algorithms jointly estimate the forward and reverse transformation between two images while minimizing the inverse consistency error-the error between the forward (reverse) transformation and the inverse of the the reverse (forward) transformation. This reduces the ambiguous correspondence between the forward and reverse transformations associated with large inverse consistency errors. In both algorithms a thin-plate spline (TPS) model is used to regularize the estimated transformations. Two-dimensional (2-D) examples are presented that show the inverse consistency error produced by the traditional unidirectional landmark TPS algorithm can be relatively large and that this error is minimized using the consistent landmark algorithm. Results using 2-D magnetic resonance imaging data are presented that demonstrate that using landmark and intensity information together produce better correspondence between medical images than using either landmarks or intensity information alone.

Algorithms↗

PubMed1992

A quantitative study of the Ca2+/calmodulin sensitivity of adenylyl cyclase in Aplysia, Drosophila, and rat.

Studies in Aplysia and Drosophila have suggested that Ca2+/calmodulin-sensitive adenylyl cyclase may act as a site of convergence for the cellular representations of the conditioned stimulus (Ca2+ influx) and unconditioned stimulus (facilitatory transmitter) during elementary associative learning. This hypothesis predicts that the rise in intracellular free Ca2+ concentration produced by spike activity during the conditioned stimulus will cause an increase in the activity of adenylyl cyclase. However, published values for the Ca2+ sensitivity of Ca2+/calmodulin-sensitive adenylyl cyclase in mammals and in Drosophila vary widely. The difficulty in evaluating whether adenylyl cyclase would be activated by physiological elevations in intracellular Ca2+ levels is in part a consequence of the use of Ca2+/EGTA buffers, which are prone to several types of errors. Using a procedure that minimizes these errors, we have quantified the Ca2+ sensitivity of adenylyl cyclase in membranes from Aplysia, Drosophila, and rat brain with purified species-specific calmodulins. In all three species, adenylyl cyclase was activated by an increase in free Ca2+ concentration in the range caused by spike activity. Ca2+ sensitivity was dependent on both calmodulin concentration and Mg2+ concentration. Mg2+ raised the threshold for adenylyl cyclase activation by Ca2+ but also acted synergistically with Ca2+ to activate maximally adenylyl cyclase.

Adenylyl Cyclases↗

PubMed2002

A Bayesian framework for sensory adaptation.

Adaptation allows biological sensory systems to adjust to variations in the environment and thus to deal better with them. In this article, we propose a general framework of sensory adaptation. The underlying principle of this framework is the setting of internal parameters of the system such that certain prespecified tasks can be performed optimally. Because sensorial inputs vary probabilistically with time and biological mechanisms have noise, the tasks could be performed incorrectly. We postulate that the goal of adaptation is to minimize the number of task errors. This minimization requires prior knowledge of the environment and of the limitations of the mechanisms processing the information. Because these processes are probabilistic, we formulate the minimization with a Bayesian approach. Application of this Bayesian framework to the retina is successful in accounting for a host of experimental findings.

Adaptation, Physiological↗

PubMed2005

Designing a tracking system based on cognitive theory of error.

We will present an application for tracking research samples that has been designed based upon prior research in cognitive theories on error that has been applied successfully to fields such as aviation and anesthesiology. By anticipating where the errors are likely to occur in the human-computer interaction and workflow, we hope to reduce number of errors and minimize the effects of inevitable errors.

Biomedical Research↗

PubMed1987

Development and implementation of a human accuracy program in patient foodservice.

For many years, industry has utilized the concept of human error rates to monitor and minimize human errors in the production process. A consistent quality-controlled product increases consumer satisfaction and repeat purchase of product. Administrative dietitians have applied the concepts of using human error rates (the number of errors divided by the number of opportunities for error) at four hospitals, with a total bed capacity of 788, within a tertiary-care medical center. Human error rate was used to monitor and evaluate trayline employee performance and to evaluate layout and tasks of trayline stations, in addition to evaluating employees in patient service areas. Long-term employees initially opposed the error rate system with some hostility and resentment, while newer employees accepted the system. All employees now believe that the constant feedback given by supervisors enhances their self-esteem and productivity. Employee error rates are monitored daily and are used to counsel employees when necessary; they are also utilized during annual performance evaluation. Average daily error rates for a facility staffed by new employees decreased from 7% to an acceptable 3%. In a facility staffed by long-term employees, the error rate increased, reflecting improper error documentation. Patient satisfaction surveys reveal satisfaction, for tray accuracy increased from 88% to 92% in the facility staffed by long-term employees and has remained above the 90% standard in the facility staffed by new employees.

Consumer Behavior↗

PubMed2004

A systems approach to error prevention in medicine.

Minimization of medical errors is at the core of all clinical medical practices. The first tenet of care is to do no harm. The enormous complexity of modern medical care has made error detection and management extremely difficult. Traditional deterministic methods of solving the "error issue" cannot cope with the huge number of potential errors that are possible. Systems thinking and approach to error reduction provides a different avenue for tackling this challenging dilemma. The intent of this article is to introduce a systems view of medical errors and to explain how it can provide new insights about dealing with massively complex organizations such as the healthcare system. Important features include an understanding of system relationships, sources of error, human components, optimization versus perfection in systems and the interrelationships between human and system processes.

Delivery of Health Care↗

PubMed1998

Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine.

Minimal measurement error (reliability) during the collection of interval- and ratio-type data is critically important to sports medicine research. The main components of measurement error are systematic bias (e.g. general learning or fatigue effects on the tests) and random error due to biological or mechanical variation. Both error components should be meaningfully quantified for the sports physician to relate the described error to judgements regarding 'analytical goals' (the requirements of the measurement tool for effective practical use) rather than the statistical significance of any reliability indicators. Methods based on correlation coefficients and regression provide an indication of 'relative reliability'. Since these methods are highly influenced by the range of measured values, researchers should be cautious in: (i) concluding acceptable relative reliability even if a correlation is above 0.9; (ii) extrapolating the results of a test-retest correlation to a new sample of individuals involved in an experiment; and (iii) comparing test-retest correlations between different reliability studies. Methods used to describe 'absolute reliability' include the standard error of measurements (SEM), coefficient of variation (CV) and limits of agreement (LOA). These statistics are more appropriate for comparing reliability between different measurement tools in different studies. They can be used in multiple retest studies from ANOVA procedures, help predict the magnitude of a 'real' change in individual athletes and be employed to estimate statistical power for a repeated-measures experiment. These methods vary considerably in the way they are calculated and their use also assumes the presence (CV) or absence (SEM) of heteroscedasticity. Most methods of calculating SEM and CV represent approximately 68% of the error that is actually present in the repeated measurements for the 'average' individual in the sample. LOA represent the test-retest differences for 95% of a population. The associated Bland-Altman plot shows the measurement error schematically and helps to identify the presence of heteroscedasticity. If there is evidence of heteroscedasticity or non-normality, one should logarithmically transform the data and quote the bias and random error as ratios. This allows simple comparisons of reliability across different measurement tools. It is recommended that sports clinicians and researchers should cite and interpret a number of statistical methods for assessing reliability. We encourage the inclusion of the LOA method, especially the exploration of heteroscedasticity that is inherent in this analysis. We also stress the importance of relating the results of any reliability statistic to 'analytical goals' in sports medicine.

Bias↗

PubMed2006

Use of biomarkers in epidemiologic studies: minimizing the influence of measurement error in the study design and analysis.

The inclusion of biomarkers measured on the continuous scale, such as endogenous sex hormones or antioxidant levels, has become common in epidemiologic studies, and introduces additional sources of error that are specific to biomarkers. This includes error associated with specimen collection, processing, and storage; laboratory error (both within and between batch); and variability in the biomarker levels over time within an individual. In this review, we discuss and recommend study design and analytic strategies to deal with these sources of measurement error. In particular we describe methods to prevent or minimize some sources of error through appropriate sample collection and storage, communication with the laboratory, proper batching of samples, and participant matching. We also discuss how to quantify error related to biomarkers, focusing on issues of quality control, pilot studies, and how to measure within-person stability over time. Further, we discuss analytic issues for dealing with laboratory and within-person variability. Finally we recommend that journals standardize the reporting of biomarker assays in scientific manuscripts.

Biomarkers↗

PubMed2005

Feedforward neural network models for handling class overlap and class imbalance.

This paper proposes a framework for training feedforward neural network models capable of handling class overlap and imbalance by minimizing an error function that compensates for such imperfections of the training set. A special case of the proposed error function can be used for training variance-controlled neural networks (VCNNs), which are developed to handle class overlap by minimizing an error function involving the class-specific variance (CSV) computed at their outputs. Another special case of the proposed error function can be used for training class-balancing neural networks (CBNNs), which are developed to handle class imbalance by relying on class-specific correction (CSC). VCNNs and CBNNs are compared with conventional feedforward neural networks (FFNNs), quantum neural networks (QNNs), and resampling techniques. The properties of VCNNs and CBNNs are illustrated by experiments on artificial data. Various experiments involving real-world data reveal the advantages offered by VCNNs and CBNNs in the presence of class overlap and class imbalance.

Artifacts↗

PubMed1993

Operator error in a level coded myoelectric control channel.

Two forms of error exist in the level coded myoelectric control channel: system error and operator error. Currently in level coded (3-state) myoelectric prosthesis, target and switching level settings are optimized for the presence of system error only. In this study, system error was minimized in order to examine operator error. The magnitude of the operator error was found to exceed the magnitude of the experimental system error as well as the system error associated with a typical prosthesis control unit. These findings suggest that operator error should be considered when optimizing target levels and decision boundaries for level coded myoelectric prosthesis controllers. Since the operator response was estimated to be normally distributed, it is described by its mean and standard deviation. This information can be used to determine the desired optimal settings.

Arm↗

PubMed1995

Extreme derangements of acid-base balance in exercise: advantages and limitations of the Stewart analysis.

The acid-base analysis method described by Stewart (1981) was applied to the greyhound, an animal that undergoes large changes in intra- and extracellular hydrogen ion concentrations during a race. Increases in plasma [H+] especially during the first 15 min of recovery, induced by increases in lactate concentration in the plasma, were reduced by lowering of PCO2 (hyperventilation) and removal of Cl- from the plasma. [H+] calculated by the Stewart method is similar to that measured directly with a pH electrode when the strong ion difference is within 10 meq/L of resting values (approximately 40 meq/L); thus the measured independent variables were sufficient to account for the [H+] using the Stewart analysis. When the strong ion difference became lower than 30 meq/L, increased variability between measured and calculated [H+] occurred. An error analysis demonstrated the importance of minimizing measurement error of all independent variables, including as many strong and weak electrolytes as possible in the analyses, using the most accurate dissociation constants possible, and understanding the dissociation behavior of the weak electrolytes, especially the plasma proteins, when using the Stewart analysis. The Stewart method of analyzing acid-base balance can contribute to improved training methods for obtaining maximum exercise performance.

Acid-Base Equilibrium↗

PubMed1995

Color quantification in angioscopic video images.

Colors in video representations of angioscopic images are up until now described by an human observer. Differences in settings of the monitor and the inherent poor ability of the human eye to classify colors objectively results in a very poor intraobserver as well as interobserver variability. A PC-based method is described to measure colors in a video image and to present the results in a novel C-diagram. Results with this method for standard calibrated colors are given. Possible sources of error are discussed and methods to minimize these errors are presented.

Algorithms↗

PubMed1995

Application of optimized pattern recognition units in EEG analysis: common optimization of preprocessing and weights of neural networks as well as structure optimization.

The main goal of this study is to demonstrate the possibility of training the Neural Network (multilayer perceptron) classifier and preprocessing units simultaneously, i.e., that properties of preprocessing are chosen automatically during the training phase. In the first realization step, adaptive recursive estimation of the power within a frequency band was used as a preprocessing unit. To improve the efficiency of special units, the power and momentary frequency estimation was replaced by methods that are based on adaptive Hilbert transformers. The strategy was developed to obtain optimized recognition units that can be efficiently integrated into strategies for monitoring the cerebral status of neonates. Therefore, applications (e.g., in neonatal EEG pattern recognition) will be shown. Additionally, a method of minimizing the error function was used, where this minimization is based on optimizing the network structure. The results of structure optimization in the field of EEG pattern recognition in epileptic patients can be demonstrated.

Algorithms↗