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At least 1,567 records · Page 87Linked to original sources
PubMed2000

Gait event detection for FES using accelerometers and supervised machine learning.

Rule based detectors were used with a single cluster of accelerometers attached to the shank for the real time detection of the main phases of normal gait during walking. The gait phase detectors were synthesized from two rule induction algorithms, Rough Sets (RS) and Adaptive Logic Networks (ALNs), and compared with to a previously reported stance/swing detector based on a hand crafted, rule based algorithm. Data was sampled at 100 Hz and the detection errors determined at each sample for 50 steps. For three able bodied subjects, the sample by sample accuracy of stance/swing detection ranged within 94-97%, 87-94%, and 87-95% for the RS, ALN, and the handcrafted methods, respectively. A heuristically formulated postdetector filter improved the RS and ALN detectors' accuracy to 98%. RS and ALN also detected five gait phases to an overall accuracy of 82-89% and 86-91%, respectively. The postdetector filter localized the errors to the phase transitions, but did not change the detection accuracy. The average duration of the error at each transition was 40 ms and 23 ms for RS and ALN, respectively. When implemented on a microcontroller, the RS-based detector executed ten times faster and required one tenth of the memory than the ALN-based detector.

Acceleration↗
PubMed2001

Benchmark data from the literature for evaluation of new glucose sensing technologies.

New glucose sensors based on various technologies are being developed to provide information for improved therapy in diabetes. There is a need to establish rational performance standards for these sensors. Frequently sampled, direct blood glucose recordings representative of blood glucose excursions in diabetes are the "gold standard." An extensive literature search revealed a limited number of diabetic and nondiabetic blood glucose recordings suitable for this purpose. Certain blood glucose recordings reflect the diversity of glycemic dynamics and provide sufficient challenge for evaluation of sensor systems. These recordings were converted into an accessible electronic format. An example is given of the use of these benchmark data to estimate aliasing error, or the error due to insufficient sampling frequency, based on a hypothetical sensor system having some properties of conventional "fingerstick" systems. Discrete sampling systems accumulate substantial aliasing error as the sampling period increases.

Biosensing Techniques↗
PubMed2006

Procedure to normalize data for benchmarking.

INTRODUCTION: The hospital billing system is usually the source for reporting activity counts used in benchmarking efforts. Because billing is associated with a specific procedure, benchmarking data are often reported as procedure-days, procedure-shifts, or procedure-hours. Normalizing (usually to procedure-days) is required when comparing data for benchmarking purposes. For an institution that uses hourly billing, simply dividing procedure-hours by 24 (or procedure-shifts by 2 or 3) will underestimate the procedure-days reported by a daily billing system, because daily billing systems use the convention that any fractional day of service is rounded up to the next higher day. The purposes of this study were: (1) to simulate sets of data and determine the expected error with conversion by simple division, (2) to derive a more accurate procedure for normalizing benchmarking data, and (3) to compare the new normalization procedure to simple division, using simulated and actual data. METHODS: A reference population of simulated patient data was created using a spreadsheet to generate random start times paired with actual procedure durations (eg, hours of mechanical ventilation) for 5,000 patients. The spreadsheet calculated "true" billable procedure-days and procedure-shifts from the simulated procedure-hours. Next, a resampling procedure was used to simulate the effect of submitting benchmarking data based on various numbers of patients. The resulting sets of data were used to examine the association between sample size and conversion error when converting from procedure-hours to procedure-days and to generate an alternative conversion procedure that uses linear regression to estimate procedure-days from procedure-hours. An additional regression equation was generated from actual patient data, using simultaneously recorded procedure-hours and procedure-days. The set of mean conversion errors for the 2 regression equations was compared using the Mann-Whitney rank sum test. RESULTS: In general, conversion errors (both systematic and random errors) were smaller with larger sample sizes and with longer service periods, approaching an asymptote at a sample size greater than about 20. Using division, the conversion errors for a sample size of 100 were +/-16% for hourly reporting, +/-11% for 8-hour shifts, and +/-8% for 12-hour shifts. The regression equations for conversion derived from simulated data were as follows. For hourly billing, procedure-days = +/-0.237 + (0.049) (procedure-hours). For 8-hour shifts, procedure-days = +/-0.205 + (0.372) (procedure-shifts). For 12-hour shifts, procedure-days = +/-0.114 + (0.541) (procedure-shifts). Using those regression equations, the conversion errors for a sample size of 100 were +/-1% for hourly reporting, +/-0.2% for 8-hour shifts, and +/-0.2% for 12-hour shifts. The regression equation (for hourly billing) derived from simulated data gave better results than did the equation derived from actual data (median error 0.39 vs +/-2.92, p = 0.013).

Benchmarking↗
PubMed2001

A novel method to compensate for different amplification efficiencies between patient DNA samples in quantitative real-time PCR.

Quantification of residual disease by real-time polymerase chain reaction (PCR) will become a pivotal tool in the development of patient-directed therapy. In recent years, various protocols to quantify minimal residual disease in leukemia or lymphoma patients have been developed. These assays assume that PCR efficiencies are equal for all samples. Determining t(14;18) and albumin reaction efficiencies for sixteen follicular lymphoma patient samples revealed higher efficiencies for blood samples than for lymph node samples in general. However, within one sample both reactions had equivalent efficiencies. Differences in amplification efficiencies between patient samples (low efficiencies) and the calibrator in quantitative analyses result in the underestimation of residual disease in patient samples whereby the weakest positive patient samples are at highest error. Based on these findings for patient samples, the efficiency compensation control was developed. This control includes two reference reactions in a multiplex setting, specific for the beta-actin and albumin housekeeping genes that are present in a constant ratio within DNA templates. The difference in threshold cycle values for both reference reactions, ie, the Ct(2) value, is dependent on the amplification efficiency, and is used to compensate for efficiency differences between patient samples and the calibrator. The beta-actin reference reaction is also used to normalize for DNA input. Furthermore, the efficiency compensation control facilitates identification of patient samples that are so contaminated with PCR inhibitory compounds that different amplification reactions are affected to a different extent. Accurate quantitation of residual disease in these samples is therefore impossible with the current quantitative real-time PCR protocols. Identification and exclusion of these inadequate samples will be of utmost importance in quantitative retrospective studies, but even more so, in future molecular diagnostic analyses.

Actins↗
PubMed2006

Analysis of the effect of particle size on polymorphic quantitation by Raman spectroscopy.

Raman spectroscopy has been widely used to monitor various aspects of the crystallization process. Although it has long been known that particle size can influence Raman signal, relatively little research has been conducted in this area, in particular for mixtures of organic materials. The aim of this study was to investigate the effect of particle size on quantification of polymorphic mixtures. Several sets of calibration samples containing different particle size fractions were prepared and Raman spectra were collected with different probes. Calibration models were built using both univariate and multivariate analysis. It was found that, for a single component system, Raman intensity decreased with increasing particle size. For mixtures, calibration models generated from the same particle size distribution as the sample yielded relatively good predictions of the actual sample composition. However, if the particle sizes of the calibration and unknown samples were different, prediction errors resulted. For extreme differences in particle sizes, prediction errors of up to 20% were observed. Prediction errors could be minimized by changing the sampling optics employed.

Journal Article↗
PubMed1999

Fidelity of polymerase chain reaction-direct sequencing analysis of damaged forensic samples.

Polymerase chain reaction (PCR) direct sequence analysis was performed on aged forensic samples, six or thirteen years old. This method allowed unambiguous genetic typing, but PCR products from such samples showed several artifacts. Control samples generated sequence ambiguities at a frequency of 1 in 567 bases, but the aged samples had an error frequency about 30-fold higher. In order to study the molecular composition of these aged DNA samples, reversed-phase high performance liquid chromatography (HPLC) was performed. Reduced amounts of the four DNA bases were observed and anomalous peaks were found. These peaks were analyzed by ionization mass spectrometry and identified as molecular products of DNA oxidation. The frequency of sequencing artifacts was found to be proportional to the decay of the PCR templates. Although PCR fidelity is a relevant concern in the forensic analysis of damaged samples, our data indicate that the risk of mistyping is circumventable by sequencing both strands and by performing replicate amplifications from the same PCR template.

Base Sequence↗
PubMed1981

Logical reasoning deficits in schizophrenia and brain damage.

Von Domarus and Arieti have theorized that failure to reason by conventional logical rules is at the root of schizophrenic thought disorder, but the available research on this view is inconclusive. We compared the performance of schizophrenics (N = 100), brain-damaged patients (N = 50) and psychiatric controls (N = 50) on closely matched measures of Overexpansive and "Von Domarus" (similarity implies identity) syllogistic reasoning errors. Before the samples were matched for education and intelligence, the brain-damaged and schizophrenic patients made more Overexpansive errors than the controls, but the Von Domarus error difference was not significant. After matching, both differences were nonsignificant. The results indicate that inability to use syllogistic reasoning properly is probably not the root cause of schizophrenic thought disorder.

Adult↗
PubMed2005

[Application of wavelet packets analysis-interpolation-RBF to the simultaneous determination of Fe, Mn, Cu and Zn in aluminous-alloy].

A new approach was proposed so that noises invisible spectra are eliminated by wavelet packets, and the specimen numbers of calibration samples are increased by linear interpolation. It can used to solve problems of few specimen numbers and many variables in simultaneous spectrophotometric determination. Thus forecasting resultant veracity is improved. The contents of Fe, Mn, Cu and Zn in aluminous-alloy was determined simultaneously by using wavelet packets analysis-linear interpolation-RBF (radial basis function) neural networks (WPA-Interp-RBF). Wavelet packets analysis can eliminate noises to a desired level. Linear interpolation makes specimenof training samples cover recognizable room better. So RBF can abstract more characteristic information and improve its performance. Relative error(RE) of sample is reduced remarkably with desired results.

English Abstract↗
PubMed1991

Minimising errors in clinical studies by proper selection of sample size.

In the planning of a clinical trial, the statistical aspects of the choice of sample size should be considered. The meaning of statistical terms such as Type I and Type II errors, significance and power are explained. Formulae are given for calculating the required sample size for parallel groups' designs (two independent samples) and matched pair or cross-over designs for both quantitative and qualitative responses. Samples size tables are given with instructions for their use and there are four worked examples. The sample size for a trial depends on the specification of the levels of significance and power and the size of the difference the trial is designed to detect, and these can be somewhat arbitrary. Furthermore, it is often necessary to estimate the standard deviation on the basis of limited information. Thus, the sample size required for a trial cannot be determined precisely, and there can be no exactly right or wrong sample size. However, sensible consideration of sample size should ensure that the trial is not so small as to make the results trivial, nor so large as to be unethical or a waste of resources.

Clinical Trials as Topic↗
PubMed1999

Flexible flat feet in children: a real problem?

OBJECTIVES: To estimate the prevalence of flexible flat feet in the provincial population of 4- to 13-year-old schoolchildren and the incidence of treatments considered unnecessary. SETTING: Province of Málaga, Spain. METHODS: We examined and graded by severity a sample of 1181 pupils taken from a total population of 198 858 primary schoolchildren (CI: 95%; margin of error: 5%). The sample group was separated into three 2-year age groups: 4 and 5 years, 8 and 9 years, and 12 and 13 years. The plantar footprint was classified according to Denis1 into three grades of flat feet: grade 1 in which support of the lateral edge of the foot is half that of the metatarsal support; grade 2 in which the support of the central zone and forefoot are equal; and grade 3 in which the support in the central zone of the foot is greater than the width of the metatarsal support. The statistical analysis for the evaluation of the differences between the groups was performed with Student's t and chi2 tests as appropriate. RESULTS: The prevalence of flat feet was 2.7%. Of the 1181 children sampled, 168 children (14.2%) were receiving orthopedic treatment, but only 2.7% had diagnostic criteria of flat feet. When we inspected the sample, we found that a number of children were being treated for flat feet with boots and arch supports. Most of them did not have a flat plantar footprint according to the criteria that we used for this work. Furthermore, in the group of children that we diagnosed as having flat feet, only 28.1% were being treated. We found no significant differences between the number of children receiving orthopedic treatments and the presence or absence of a flat plantar footprint. Children who were overweight in the 4- and 5-year-old group showed an increased prevalence for flat feet as diagnosed by us. CONCLUSION: The data suggest that an excessive number of orthopedic treatments had been prescribed in the province. When extrapolated to the 1997 population of schoolchildren within the age groups studied the figures suggested that approximately 28 167 children in Málaga province probably would have been receiving orthopedic treatments with boots and insoles at the time of our study. Consequently, the total expenditure on orthopedic boots and insoles that year could be estimated as 676 008 000 pesetas ($4 447 422 in US currency).

Adolescent↗
PubMedDate not supplied

Nurses' perceptions of causes of medication errors and barriers to reporting.

This study describes nurses' perceptions about medication errors and the effects of physician order entry and barcode medication administration on medication errors. A convenience sample of 61 medical-surgical nurses was surveyed. All nurses surveyed perceived that information technology decreases medication errors. However, medication errors continue to occur despite the availability of sophisticated information technology systems.

Adverse Drug Reaction Reporting Systems↗
PubMed2007

Repeated measurement sampling in genetic association analysis with genotyping errors.

Genotype misclassification occurs frequently in human genetic association studies. When cases and controls are subject to the same misclassification model, Pearson's chi-square test has the correct type I error but may lose power. Most current methods adjusting for genotyping errors assume that the misclassification model is known a priori or can be assessed by a gold standard instrument. But in practical applications, the misclassification probabilities may not be completely known or the gold standard method can be too costly to be available. The repeated measurement design provides an alternative approach for identifying misclassification probabilities. With this design, a proportion of the subjects are measured repeatedly (five or more repeats) for the genotypes when the error model is completely unknown. We investigate the applications of the repeated measurement method in genetic association analysis. Cost-effectiveness study shows that if the phenotyping-to-genotyping cost ratio or the misclassification rates are relatively large, the repeat sampling can gain power over the regular case-control design. We also show that the power gain is not sensitive to the genetic model, genetic relative risk and the population high-risk allele frequency, all of which are typically important ingredients in association studies. An important implication of this result is that whatever the genetic factors are, the repeated measurement method can be applied if the genotyping errors must be accounted for or the phenotyping cost is high.

Case-Control Studies↗
PubMed2003

Power and sample size calculations for generalized regression models with covariate measurement error.

Covariate measurement error is often a feature of scientific data used for regression modelling. The consequences of such errors include a loss of power of tests of significance for the regression parameters corresponding to the true covariates. Power and sample size calculations that ignore covariate measurement error tend to overestimate power and underestimate the actual sample size required to achieve a desired power. In this paper we derive a novel measurement error corrected power function for generalized linear models using a generalized score test based on quasi-likelihood methods. Our power function is flexible in that it is adaptable to designs with a discrete or continuous scalar covariate (exposure) that can be measured with or without error, allows for additional confounding variables and applies to a broad class of generalized regression and measurement error models. A program is described that provides sample size or power for a continuous exposure with a normal measurement error model and a single normal confounder variable in logistic regression. We demonstrate the improved properties of our power calculations with simulations and numerical studies. An example is given from an ongoing study of cancer and exposure to arsenic as measured by toenail concentrations and tap water samples.

Arsenic↗
PubMed1976

Bubbles in samples for blood gas determinations. A potential source of error.

The presence of small gas bubbles in devices used to collect blood gas samples is considered. A gas bubble whose relative volume is 0.5 to 1% or more that of the liquid in the collection device is a potential source of significant error. Relationships describing the possible magnitude of this error are derived and substantiated.

Blood↗
PubMed2001

Correction of H3+ contributions in hydrogen isotope ratio monitoring mass spectrometry.

Two fundamentally different approaches, termed "pointwise" and "peakwise," are currently used to correct hydrogen isotope ratio monitoring data for the presence of H3+ ion contributions. Consideration of the underlying assumptions shows that the peakwise approach is valid only for peaks with the same functional shape and only when background signals do not vary. The pointwise correction is much more versatile and can be used even when peak shapes and sizes, as well as background signals, vary significantly. It is not exact and is limited in accuracy by (1) the signal-broadening effects of electronic time constants, (2) the analog-to-digital conversion frequency, and (3) the highest frequency of the sample signal. To minimize errors for typical gas chromatographic signals, time constants of <500 ms and analog-to-digital sampling intervals of < or =250 ms are needed. Errors are further minimized by matching sample and standard peaks in both amplitude and D/H ratio. Using the pointwise algorithm, we demonstrate that a series of 14 homologous n-alkanes varying in concentration over a 5-fold range can be analyzed with a mean precision of 2.3 per thousand and no systematic errors.

Journal Article↗
PubMed1997

The spatial dependence of spin-echo signals.

The signals in NMR spin echoes which are refocused by 90 degrees pulses are spatially modulated. The spatial modulation is not normally observed in images or profiles obtained using Hahn or stimulated echoes, but may cause errors if the sample structure varies on the distance scale of the modulation. Localized spectra measured using stimulated echoes will also show errors under these conditions. Simple Fourier-transform arguments show that conditions which allow the modulation to become visible in an image or profile have the effect of introducing a second echo into the time-domain acquisition window. Phase cycling may be used to remove the spatial dependence of the signals.

Artifacts↗
PubMed2001

Self-affine nature of the stress-strain behavior of thin fiber networks.

The stress-strain behavior of toilet paper is studied. We find that the damaged parts of stress-strain curves possess a self-affine scaling invariance. Moreover, we find that the stress-strain behavior and the rupture line roughness are characterized by the same scaling (Hurst) exponent H, which is not universal: rather it changes from sample to sample. The variations on H are mainly due to fluctuations in the paper structure, which are larger than statistical errors within a sample. Furthermore, the same exponent governs the changes in the stress-strain curve as the strain rate increases. The fractal damage model is employed to explain experimental observations.

Journal Article↗
PubMedDate not supplied

[Average body weight and height gain rate in children from 2 to 10 years old in a rural area of the Marinilla municipality, Antioquia, Colombia. 1996-1999].

BACKGROUND: The objective of the present study was to evaluate the average growth rate (AGR) in 2 to 10 years old children (n = 259) belonging to rural families from the municipality of Marinilla (Colombia). The results will be taking into account in order to define public health polices aimed to improve the life quality conditions in rural communities. METHODS: In a descriptive longitudinal prospective study a representative sample from rural horticulture families having children aged 2 to 10 years old were selected. The confidence interval, alpha error, and over sample were 95.5 and 20%, respectively. The AGR for weight and high were evaluated according to the method by Baumgarthner, and the results were compared with the Fels Longitudinal Study reference values. RESULTS: For AGR for weight 26.8 and 28.9% of boys and girls classified in the lower 25 percentile, respectively: 60.9 and 62.8% within the 25 and 75 percentiles, and 12.3 and 8.2% in the upper percentile of boys and girls, respectively. On the other hand, for AGR for high 44.9 and 33.1% of boys and girls classified in the lower 25 percentile, 44.9 and 52.9% within the 25 and 75 percentiles, and 10.2 and 14.1% in the upper percentile of boys and girls, respectively. CONCLUSIONS: These results showed that the AGR of children in this study could not overcome their delayed weight and high measures.

Body Height↗