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At least 1,477 records · Page 82Linked to original sources
PubMed2002

Motor control impairment of the contralateral wrist in patients with unilateral chronic wrist pain.

OBJECTIVE: Assessment of the quality of fine motor control in patients with unilateral chronic wrist pain seldom focuses on the possibility that control of movements is effector independent at the cerebral level. This mechanism may be involved in an impairment of motor function in the unaffected wrist. We studied the possible motor impairment in the unaffected wrist in patients with chronic wrist pain. DESIGN: Eighteen patients with chronic wrist pain in their dominant hand and 20 healthy controls performed, using their nondominant hand, back-and-forth, left-to-right stroke patterns with a pen on a digital writing tablet connected to a computer. Fluency of movement, defined as the number of zero-crossings of the acceleration curve (pZC), average stroke size, and average velocity were calculated. RESULTS: The controls moved significantly more fluently than the patients (pZC, 0.26+/-0.07 for controls and 0.46+/-0.20 for patients; P < 0.001), suggesting that long-term afferent disturbances may compromise cerebral motor control mechanisms. CONCLUSIONS: This result is in accordance with the view that chronic pain complaints may be maintained by persistently abnormal cerebral motor control. This finding opens a new perspective on the understanding and treatment of chronic wrist pain.

Adolescent↗
PubMedDate not supplied

Palm computer demonstrates a fast and accurate means of burn data collection.

Manual biomedical data collection and entry of the data into a personal computer is time-consuming and can be prone to errors. The purpose of this study was to compare data entry into a hand-held computer versus hand written data followed by entry of the data into a personal computer. A Palm (3Com Palm IIIx, Santa, Clara, Calif) computer with a custom menu-driven program was used for the entry and retrieval of burn-related variables. These variables were also used to create an identical sheet that was filled in by hand. Identical data were retrieved twice from 110 charts 48 hours apart and then used to create an Excel (Microsoft, Redmond, Wash) spreadsheet. One time data were recorded by the Palm entry method, and the other time the data were handwritten. The method of retrieval was alternated between the Palm system and handwritten system every 10 charts. The total time required to log data and to generate an Excel spreadsheet was recorded and used as a study endpoint. The total time for the Palm method of data collection and downloading to a personal computer was 23% faster than hand recording with the personal computer entry method (P < 0.05), and 58% fewer errors were generated with the Palm method.) The Palm is a faster and more accurate means of data collection than a handwritten technique.

Burns↗
PubMed1999

Using a hand-held computer to collect data in an orthopedic outpatient clinic: a randomized trial of two survey methods.

OBJECTIVES: In a randomized study, the authors examine how data can be collected at the point of care. Specifically, examining to what extent handheld computer data collection systems introduce bias or increase respondent difficulty. METHODS: Volunteers were randomized to 1 of 2 survey methods: the hand-held computer or a paper and pencil form of similar content. Differences between group scale scores were compared using the Wilcoxon (rank sum) test. RESULTS: The hand-held computer system produced comparable scores to paper and pencil surveys. However, there was evidence of lower internal consistency reliability with the handheld computer. CONCLUSIONS: This study demonstrated the comparability of the hand-held computer methodology to the paper and pencil methodology in obtaining survey information in an ambulatory clinic. The hand-held computer method of survey data collection offers an alternative to paper methods when point-of-care administration is acceptable. Preliminary evidence shows that this method produces comparable results to paper forms.

Adolescent↗
PubMed1985

Physiological effects of plus lens application.

The prescribing of low-power spherical convex lenses for nearpoint has been advocated on the basis of associated visual and physiological responses. A review of research related to this topic reveals that the physiological effects of plus lenses are highly individualized. The purpose of this paper is to reevaluate research on this subject in the context of clinical prescribing.

Adolescent↗
PubMed2005

Relationship between visual-motor integration and spatial organization of written language and math.

PURPOSE: The relationship between visual-motor integration and academic achievement is not clearly understood. The purpose of this study was to assess the type and frequency of errors made by children with poor visual-motor integration during a written language and math task. METHODS: Eighteen children with normal visual-motor integration (> or =36%) and 19 children with low visual-motor integration (< or =16%) participated in the study. The two groups had similar ages, gender profiles, and cognitive and reading levels. Each group copied and solved math problems and copied a written passage. The errors for the math and writing task were combined into a total error score, and the time taken to complete each task was combined into a total time score. RESULTS: The low visual-motor integration group made more errors than the normal visual-motor integration group. However, the time taken to copy both tasks was not different between the two groups. A secondary analysis of the errors revealed that alignment of numbers (p = 0.02), organization of math problems (p = 0.05), and spacing errors of letters and words (p = 0.01) were more common in the low visual-motor integration group. CONCLUSIONS: The results suggest that reduced visual-motor integration may contribute to poor spatial organization of written work.

Child↗
PubMed2001

Evaluation of a program to improve the prescription-writing quality in hospital.

This paper aims to evaluate the effectiveness of a program designed to improve the quality of drug prescription-writing at a university hospital in France. Improvement actions included feed-back from yearly audits and the dissemination of recommendations on how best to write the prescriptions. A random sample of 30 stays was selected from among the hospitalizations for the year 1996. From each patient, medical records were searched for the first prescription order of the stay and its quality was assessed according to standards. A total of 872 records were relevant and included 3,289 medications. The results were compared to those obtained for the two previous years. Actions to sensitize prescribers resulted in an insufficient improvement of most indicators of prescription-writing quality with results remaining well below ideal standards. The hospital staff concerned had a positive opinion of the program which led to an awareness of prescription problems. This assessment showed that the program had a moderate impact on prescribers' practice and efforts must be continued.

Drug Prescriptions↗
PubMed2004

Iterative multimodel subimage binarization for handwritten character segmentation.

Existing binarization methods are categorized as either global or local. In this paper, we present a new category, where the image is considered a collection of subimages. Each subimage provides a statistical model for the handwritten characters that can be used to optimize the binarization of other subimages based on gray-level and stroke-run features. The proposed method uses these multimodels to iteratively arrive at the optimal threshold for each subimage. It can be applied to different types of documents where prior knowledge about the noisiness of the subimages is not available. Experimental results showed significant improvement in the binarization quality in comparison with other well-established algorithms.

Algorithms↗
PubMed2006

Velocity-image model for online signature verification.

In general, online signature capturing devices provide outputs in the form of shape and velocity signals. In the past, strokes have been extracted while tracking velocity signal minimas. However, the resulting strokes are larger and complicated in shape and thus make the subsequent job of generating a discriminative template difficult. We propose a new stroke-based algorithm that splits velocity signal into various bands. Based on these bands, strokes are extracted which are smaller and more simpler in nature. Training of our proposed system revealed that low- and high-velocity bands of the signal are unstable, whereas the medium-velocity band can be used for discrimination purposes. Euclidean distances of strokes extracted on the basis of medium velocity band are used for verification purpose. The experiments conducted show improvement in discriminative capability of the proposed stroke-based system.

Algorithms↗
PubMed2004

Effects of classifier structures and training regimes on integrated segmentation and recognition of handwritten numeral strings.

In integrated segmentation and recognition of character strings, the underlying classifier is trained to be resistant to noncharacters. We evaluate the performance of state-of-the-art pattern classifiers of this kind. First, we build a baseline numeral string recognition system with simple but effective presegmentation. The classification scores of the candidate patterns generated by presegmentation are combined to evaluate the segmentation paths and the optimal path is found using the beam search strategy. Three neural classifiers, two discriminative density models, and two support vector classifiers are evaluated. Each classifier has some variations depending on the training strategy: maximum likelihood, discriminative learning both with and without noncharacter samples. The string recognition performances are evaluated on the numeral string images of the NIST Special Database 19 and the zipcode images of the CEDAR CDROM-1. The results show that noncharacter training is crucial for neural classifiers and support vector classifiers, whereas, for the discriminative density models, the regularization of parameters is important. The string recognition results compare favorably to the best ones reported in the literature though we totally ignored the geometric context. The best results were obtained using a support vector classifier, but the neural classifiers and discriminative density models show better trade-off between accuracy and computational overhead.

Algorithms↗
PubMed2004

Image distortion analysis using polynomial series expansion.

In this paper, we derive a technique for analysis of local distortions which affect data in real-world applications. In the paper, we focus on image data, specifically handwritten characters. Given a reference image and a distorted copy of it, the method is able to efficiently determine the rotations, translations, scaling, and any other distortions that have been applied. Because the method is robust, it is also able to estimate distortions for two unrelated images, thus determining the distortions that would be required to cause the two images to resemble each other. The approach is based on a polynomial series expansion using matrix powers of linear transformation matrices. The technique has applications in pattern recognition in the presence of distortions.

Algorithms↗
PubMed2004

Online handwritten script recognition.

Automatic identification of handwritten script facilitates many important applications such as automatic transcription of multilingual documents and search for documents on the Web containing a particular script. The increase in usage of handheld devices which accept handwritten input has created a growing demand for algorithms that can efficiently analyze and retrieve handwritten data. This paper proposes a method to classify words and lines in an online handwritten document into one of the six major scripts: Arabic, Cyrillic, Devnagari, Han, Hebrew, or Roman. The classification is based on 11 different spatial and temporal features extracted from the strokes of the words. The proposed system attains an overall classification accuracy of 87.1 percent at the word level with 5-fold cross validation on a data set containing 13,379 words. The classification accuracy improves to 95 percent as the number of words in the test sample is increased to five, and to 95.5 percent for complete text lines consisting of an average of seven words.

Algorithms↗