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Fulltext A Sequential Handwriting Recognition Model Based on a Dynamically Configurable CRNN

Al-Saffar A, Awang S, Al-Saiagh W, Al-Khaleefa AS, Abed SA

Sensors (Basel), 2021 Nov 02;21(21).
PMID: 34770612 DOI: 10.3390/s21217306

Handwriting recognition refers to recognizing a handwritten input that includes character(s) or digit(s) based on an image. Because most applications of handwriting recognition in real life contain sequential text in various languages, there is a need to develop a dynamic handwriting recognition system. Inspired by the neuroevolutionary technique, this paper proposes a Dynamically Configurable Convolutional Recurrent Neural Network (DC-CRNN) for the handwriting recognition sequence modeling task. The proposed DC-CRNN is based on the Salp Swarm Optimization Algorithm (SSA), which generates the optimal structure and hyperparameters for Convolutional Recurrent Neural Networks (CRNNs). In addition, we investigate two types of encoding techniques used to translate the output of optimization to a CRNN recognizer. Finally, we proposed a novel hybridized SSA with Late Acceptance Hill-Climbing (LAHC) to improve the exploitation process. We conducted our experiments on two well-known datasets, IAM and IFN/ENIT, which include both the Arabic and English languages. The experimental results have shown that LAHC significantly improves the SSA search process. Therefore, the proposed DC-CRNN outperforms the handcrafted CRNN methods.

Matched MeSH terms: Handwriting*
Analysis of the effects and relationship of perceived handwritten signature's size, graphical complexity, and legibility with dynamic parameters for forged and genuine samples

Ahmad SM, Ling LY, Anwar RM, Faudzi MA, Shakil A

J Forensic Sci, 2013 May;58(3):724-31.
PMID: 23527753 DOI: 10.1111/1556-4029.12075

This article presents an analysis of handwritten signature dynamics belonging to two authentication groups, namely genuine and forged signature samples. Genuine signatures are initially classified based on their relative size, graphical complexity, and legibility as perceived by human examiners. A pool of dynamic features is then extracted for each signature sample in the two groups. A two-way analysis of variance (ANOVA) is carried out to investigate the effects and the relationship between the perceived classifications and the authentication groups. Homogeneity of variance was ensured through Bartlett's test prior to ANOVA testing. The results demonstrated that among all the investigated dynamic features, pen pressure is the most distinctive which is significantly different for the two authentication groups as well as for the different perceived classifications. In addition, all the relationships investigated, namely authenticity group versus size, graphical complexity, and legibility, were found to be positive for pen pressure.

Matched MeSH terms: Handwriting
A systematic review of occupational therapy intervention for handwriting skills in 4-6 year old children

Kadar M, Wan Yunus F, Tan E, Chai SC, Razaob Razab NA, Mohamat Kasim DH

Aust Occup Ther J, 2020 02;67(1):3-12.
PMID: 31799722 DOI: 10.1111/1440-1630.12626

INTRODUCTION: Handwriting skills play a significant role in all stages of an individual's life. Writing interventions should be considered at a younger age to ensure proper development of writing skills. Hence, the aims of this study is to evaluate the current evidence of occupational therapy interventions in handwriting skills for 4-6 year old children.
METHODS: Published literature was systematically searched according to PRISMA guidelines using specific key terms. Initial search identified 785 studies; however only seven met the inclusion criteria and were assessed for final review. Studies were methodologically appraised using the McMaster Critical Review Form-Quantitative Studies.
RESULTS: The review found no randomised control trial study design pertaining to the reviewed area. However, it can be seen that occupational therapy interventions for writing skills in 4-6 year old children managed to increase the targeted skills. The results were similar across samples with or without disabilities. An effective integration of occupational therapy interventions into educational curriculum was found to save both time and cost.
CONCLUSION: The long-term benefit from these interventions and the effects of these interventions on a broader spectrum of fine motor abilities need to be explored further with stronger research designs. However, the lack of studies adopting high level study designs, i.e., RCT designs means, results need to be approached with caution by occupational therapists when implementing handwriting skills intervention in practice.

Matched MeSH terms: Handwriting*
Fulltext Online handwritten signature verification using neural network classifier based on principal component analysis

Iranmanesh V, Ahmad SM, Adnan WA, Yussof S, Arigbabu OA, Malallah FL

ScientificWorldJournal, 2014;2014:381469.
PMID: 25133227 DOI: 10.1155/2014/381469

One of the main difficulties in designing online signature verification (OSV) system is to find the most distinctive features with high discriminating capabilities for the verification, particularly, with regard to the high variability which is inherent in genuine handwritten signatures, coupled with the possibility of skilled forgeries having close resemblance to the original counterparts. In this paper, we proposed a systematic approach to online signature verification through the use of multilayer perceptron (MLP) on a subset of principal component analysis (PCA) features. The proposed approach illustrates a feature selection technique on the usually discarded information from PCA computation, which can be significant in attaining reduced error rates. The experiment is performed using 4000 signature samples from SIGMA database, which yielded a false acceptance rate (FAR) of 7.4% and a false rejection rate (FRR) of 6.4%.

Matched MeSH terms: Handwriting*
AUTOMATED SYNTAX ANALYSES OF DRAWING TWO TANGENT PATTERNS IN CHILDREN WITH LOW AND AVERAGE HANDWRITING ABILITY (.)

Tabatabaey-Mashadi N, Sudirman R, Khalid PI, Lange-Küttner C

Percept Mot Skills, 2015 Jun;120(3):865-94.
PMID: 26029964

Sequential strategies of digitized tablet drawings by 6-7-yr.-old children (N = 203) of average and below-average handwriting ability were analyzed. A Beery Visual Motor Integration (BVMI) and a Bender-Gestalt (BG) pattern, each composed of two tangential shapes, were predefined into area sectors for automatic analysis and adaptive mapping of the drawings. Girls more often began on the left side and used more strokes than boys. The below-average handwriting group showed more directional diversity and idiosyncratic strategies.

Matched MeSH terms: Handwriting*
Fulltext Evaluation of organic solvents efficiency for ink samples extraction

Nur Atiqah Zaharulli

ESTEEM Academic Journal, 2020;16(2):88-95.
MyJurnal

Questioned document examination becomes a great interest and one of the broad fields in forensic science. It involves the analysis of ink, handwriting and signature examination, paper’s physical structure analysis and the ageing of a document. Ink analysis in forensic document examination is a challenging process. Questioned documents examiners are dealing with unknown source of ink and minute sample size. Ink extraction needs to be done before the ink analysis. 17 gel pen ink samples were chosen in this study. Solubility test has been done to determine the degree of solubility of ink in a variety of organic solvents. Extraction solvent optimization is a process to evaluate the efficiency of organic solvents to extract ink samples. Ethanoic acid showed the ability to dissolve most of the ink samples and displayed maximum absorbance of UV-Vis spectra.

Matched MeSH terms: Handwriting
Fulltext A new method of mark detection for software-based optical mark recognition

Loke SC, Kasmiran KA, Haron SA

PLoS One, 2018;13(11):e0206420.
PMID: 30412588 DOI: 10.1371/journal.pone.0206420

Software optical mark recognition (SOMR) is the process whereby information entered on a survey form or questionnaire is converted using specialized software into a machine-readable format. SOMR normally requires input fields to be completely darkened, have no internal labels, or be filled with a soft pencil, otherwise mark detection will be inaccurate. Forms can also have print and scan artefacts that further increase the error rate. This article presents a new method of mark detection that improves over existing techniques based on pixel counting and simple thresholding. Its main advantage is that it can be used under a variety of conditions and yet maintain a high level of accuracy that is sufficient for scientific applications. Field testing shows no software misclassification in 5695 samples filled by trained personnel, and only two misclassifications in 6000 samples filled by untrained respondents. Sensitivity, specificity, and accuracy were 99.73%, 99.98%, and 99.94% respectively, even in the presence of print and scan artefacts, which was superior to other methods tested. A separate direct comparison for mark detection showed a sensitivity, specificity, and accuracy respectively of 99.7%, 100.0%, 100.0% (new method), 96.3%, 96.0%, 96.1% (pixel counting), and 99.9%, 99.8%, 99.8% (simple thresholding) on clean forms, and 100.0%, 99.1%, 99.3% (new method), 98.4%, 95.6%, 96.2% (pixel counting), 100.0%, 38.3%, 51.4% (simple thresholding) on forms with print artefacts. This method is designed for bubble and box fields, while other types such as handwriting fields require separate error control measures.

Matched MeSH terms: Handwriting
Fulltext The effect of "group detailing" on drug prescribing in primary care

Mastura I, Teng CL

Med J Malaysia, 2008 Oct;63(4):315-8.
PMID: 19385492

The quality of physician prescribing is suboptimal. Patients are at risk of potentially adverse reaction because of inappropriate or writing error in the drug prescriptions. We assess the effect of "group academic detailing" to reduce writing drug name using brand name and short form in the drug prescriptions in a controlled study at two primary health care clinics in Negeri Sembilan. Five medical officers in Ampangan Health Clinic received an educational intervention consisting of group academic detailing from the resident Family Medicine Specialist, as well as a drug summary list using generic names. The academic detailing focused on appropriate prescribing habit and emphasized on using the full generic drug name when writing the drug prescription. Analyses were based on 3371 prescriptions that were taken from two clinics. The other health clinic was for comparison. The prescribing rates were assessed by reviewing the prescriptions (two months each for pre- and post-intervention phase). Statistically significant reduction in writing prescription using brand name and using short form were observed after the educational intervention. Writing prescription using brand name for pre- and postintervention phase were 33.9% and 19.0% (postintervention vs pre-intervention RR 0.56, 95% CI 0.48 to 0.66) in the intervention clinic. Prescription writing using any short form for pre- and post-intervention phase were 49.2% and 29.2% (post-intervention vs pre-intervention RR 0.59, 95% CI 0.53 to 0.67). This low cost educational intervention focusing on prescribing habit produced an important reduction in writing prescription using brand name and short form. Group detailing appears to be feasible in the public health care system in Malaysia and possibly can be used for other prescribing issues in primary care.

Matched MeSH terms: Handwriting
Fulltext Parkinson's Disease Diagnosis and Severity Assessment Using Ground Reaction Forces and Neural Networks

Veeraragavan S, Gopalai AA, Gouwanda D, Ahmad SA

Front Physiol, 2020;11:587057.
PMID: 33240106 DOI: 10.3389/fphys.2020.587057

Gait analysis plays a key role in the diagnosis of Parkinson's Disease (PD), as patients generally exhibit abnormal gait patterns compared to healthy controls. Current diagnosis and severity assessment procedures entail manual visual examinations of motor tasks, speech, and handwriting, among numerous other tests, which can vary between clinicians based on their expertise and visual observation of gait tasks. Automating gait differentiation procedure can serve as a useful tool in early diagnosis and severity assessment of PD and limits the data collection to solely walking gait. In this research, a holistic, non-intrusive method is proposed to diagnose and assess PD severity in its early and moderate stages by using only Vertical Ground Reaction Force (VGRF). From the VGRF data, gait features are extracted and selected to use as training features for the Artificial Neural Network (ANN) model to diagnose PD using cross validation. If the diagnosis is positive, another ANN model will predict their Hoehn and Yahr (H&Y) score to assess their PD severity using the same VGRF data. PD Diagnosis is achieved with a high accuracy of 97.4% using simple network architecture. Additionally, the results indicate a better performance compared to other complex machine learning models that have been researched previously. Severity Assessment is also performed on the H&Y scale with 87.1% accuracy. The results of this study show that it is plausible to use only VGRF data in diagnosing and assessing early stage Parkinson's Disease, helping patients manage the symptoms earlier and giving them a better quality of life.

Matched MeSH terms: Handwriting
Visual-perceptual-kinesthetic inputs on influencing writing performances in children with handwriting difficulties

Tse LF, Thanapalan KC, Chan CC

Res Dev Disabil, 2014 Feb;35(2):340-7.
PMID: 24333804 DOI: 10.1016/j.ridd.2013.11.013

This study investigated the role of visual-perceptual input in writing Chinese characters among senior school-aged children who had handwriting difficulties (CHD). The participants were 27 CHD (9-11 years old) and 61 normally developed control. There were three writing conditions: copying, and dictations with or without visual feedback. The motor-free subtests of the Developmental Test of Visual Perception (DTVP-2) were conducted. The CHD group showed significantly slower mean speeds of character production and less legibility of produced characters than the control group in all writing conditions (ps<0.001). There were significant deteriorations in legibility from copying to dictation without visual feedback. Nevertheless, the Group by Condition interaction effect was not statistically significant. Only position in space of DTVP-2 was significantly correlated with the legibility among CHD (r=-0.62, p=0.001). Poor legibility seems to be related to the less-intact spatial representation of the characters in working memory, which can be rectified by viewing the characters during writing. Visual feedback regarding one's own actions in writing can also improve legibility of characters among these children.

Matched MeSH terms: Handwriting*
The use of graphic rules in grade one to help identify children at risk of handwriting difficulties

Khalid PI, Yunus J, Adnan R, Harun M, Sudirman R, Mahmood NH

Res Dev Disabil, 2010 Nov-Dec;31(6):1685-93.
PMID: 20554150 DOI: 10.1016/j.ridd.2010.04.005

Previous researches on elementary grade handwriting revealed that pupils employ certain strategy when writing or drawing. The relationship between this strategy and the use of graphic rules has been documented but very little research has been devoted to the connection between the use of graphic rules and handwriting proficiency. Thus, this study was conducted to investigate the relative contribution of the use of graphic rules to the writing ability. A sample of 105 first graders who were average printers and 65 first graders who might experience handwriting difficulty, as judged by their teachers, of a normal primary school were individually tested on their use of graphic rules. It has been found that pupils who are below average printers use more non-analytic strategy than average printers to reproduce the figures. The results also reveal that below average printers do not acquire the graphic principles that foster an analytic approach to production skills. Although the findings are not sufficient to allow definitive conclusions about handwriting ability, it can be considered as one of the screening measures in identifying pupils who are at risk of handwriting difficulties.

Matched MeSH terms: Handwriting*
Extraction of dynamic features from hand drawn data for the identification of children with handwriting difficulty

Khalid PI, Yunus J, Adnan R

Res Dev Disabil, 2010 Jan-Feb;31(1):256-62.
PMID: 19854613 DOI: 10.1016/j.ridd.2009.09.009

Studies have shown that differences between children with and without handwriting difficulties lie not only in the written product (static data) but also in dynamic data of handwriting process. Since writing system varies among countries and individuals, this study was conducted to determine the feasibility of using quantitative outcome measures of children's drawing to identify children who are at risk of handwriting difficulties. A sample of 143 first graders of a normal primary school was investigated regarding their handwriting ability. The children were divided into two groups: test and control. Ten children from test group and 40 children from control group were individually tested for their Visual Motor Integration skills. Analysis on dynamic data indicated significant differences between the two groups in temporal and spatial measures of the drawing task performance. Thus, kinematic analysis of children's drawing is feasible to provide performance characteristic of handwriting ability, supporting its use in screening for handwriting difficulty.

Matched MeSH terms: Handwriting*
Investigation of class characteristics in English handwriting of the three main racial groups: Chinese, Malay and Indian in Singapore

Cheng N, Lee GK, Yap BS, Lee LT, Tan SK, Tan KP

J Forensic Sci, 2005 Jan;50(1):177-84.
PMID: 15831016

This paper investigated the class characteristics in English handwriting of the Chinese, Malays and Indians in Singapore, many of whom learned their native language as a second language. One hundred and fifty-four handwriting exemplars were collected and features such as letter designs, pen-lifts, letter spacing and embellishments were studied. A number of characteristic features peculiar to the individual racial group were identified, which confirmed the impact of their native language writing systems on English handwriting.

Matched MeSH terms: Handwriting*
Separation of prescribing and dispensing in Malaysia: a summary of arguments

Shafie AA, Hassali MA, Azhar S, See OG

Res Social Adm Pharm, 2012 May-Jun;8(3):258-62.
PMID: 21824823 DOI: 10.1016/j.sapharm.2011.06.002

The role of pharmacists has transformed significantly because of changes in pharmacists' training and population health demands. Within this context, community pharmacists are recognized as important health personnel for the provision of extended health services. Similarly, in Malaysia, the need to transform community pharmacy practice has been discussed by all interested parties; however, the transition has been slow due in part to the nonexistence of a dispensing separation policy between pharmacists and medical doctors in private community practices. For decades, medical doctors in private community practices have had the right to prescribe and dispense, thus diluting the role of community pharmacists because of overlapping roles. This article explores dispensing separation in Malaysia and, by taking into account the needs of health professionals and health care consumers, suggests a mechanism for how dispensing separation practice can be implemented.

Matched MeSH terms: Handwriting
Glove-based approach to online signature verification

Kamel NS, Sayeed S, Ellis GA

IEEE Trans Pattern Anal Mach Intell, 2008 Jun;30(6):1109-13.
PMID: 18421114 DOI: 10.1109/TPAMI.2008.32

Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel on-line signature verification system using the Singular Value Decomposition (SVD) numerical tool for signature classification and verification is presented. The proposed technique is based on the Singular Value Decomposition in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, so the effective dimensionality of A can be reduced. Having modeled the data glove signature through its r-principal subspace, signature authentication is performed by finding the angles between the different subspaces. A demonstration of the data glove is presented as an effective high-bandwidth data entry device for signature verification. This SVD-based signature verification technique is tested and its performance is shown to be able to recognize forgery signatures with a false acceptance rate of less than 1.2%.

Matched MeSH terms: Handwriting*

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