Graphics Tablet Research Articles

Do individual characteristics influence the beta-elliptic modeling errors during ellipse drawing movements?

This paper investigates whether age, gender, and degree of familiarity with writing have an influence on the Beta-elliptic model errors during hand-drawing on a graphical tablet. A database of elliptical hand drawing movements was built within a sample of 99 participants aged between 19 and 85 years. Using the Beta-elliptic model, the velocity profile was modeled by overlapped Beta functions and the drawing trajectory was segmented between velocity extrema and each segment geometry was modeled by elliptic arcs. Average absolute and relative geometric, curvature and curvilinear velocity errors were 0.27 mm, 0.68%, 4.54 mm, 0.48%, 4.68 mm/s, and 8.79% respectively. Statistical analyses revealed not significant or low correlation between modeling errors and age and movement velocity, and no significant or low error differences according to gender or degree of familiarity with writing.

Teaching University Physics Courses During the Coronavirus Pandemic (COVID-19)

The pandemic caused by COVID-19 has induced health emergencies followed by changes in social life and education. The transition to online teaching might be harder or easier depending on the situation in a particular country, as well as on the curriculum of teaching subjects and teaching methods that are used. In this paper the methods used in summer semester of 2020 at the University of Novi Sad are presented. For teaching different theoretical physics courses, the Discord platform and graphics tablet have been used. This analysis shows that although online teaching in this form may not be a suitable replacement, it has certain advantages compared to standard classroom teaching.

Using computerized spiral analysis to evaluate deep brain stimulation outcomes in Parkinson disease

ObjectiveTo determine whether spiral analysis can monitor the effects of deep brain stimulation (DBS) in Parkinson disease (PD) and provide a window on clinical features that change post-operatively. Clinical evaluation after DBS is subjective and insensitive to small changes. Spiral analysis is a computerized test that quantifies kinematic, dynamic, and spatial aspects of spiral drawing. Validated computational indices are generated and correlate with a range of clinically relevant motor findings. These include measures of overall clinical severity (Severity), bradykinesia and rigidity (Smoothness), amount of tremor (Tremor), irregularity of drawing movements (Variability), and micrographia (Tightness). MethodsWe retrospectively evaluated the effect of subthalamic nucleus (STN) (n = 66) and ventral intermediate thalamus (Vim) (n = 10) DBS on spiral drawing in PD subjects using spiral analysis. Subjects freely drew ten spirals on plain paper with an inking pen on a graphics tablet. Five spiral indices (Severity, Smoothness, Tremor, Variability, Tightness) were calculated and compared pre- and post-operatively using Wilcoxon-rank sum tests, adjusting for multiple comparisons. ResultsSeverity improved after STN and Vim DBS (p < 0.005). Smoothness (p < 0.01) and Tremor (p < 0.02) both improved after STN and Vim DBS. Variability improved only with Vim DBS. Neither STN nor Vim DBS significantly changed Tightness. ConclusionsAll major spiral indices, except Tightness, improved after DBS. This suggests spiral analysis monitors DBS effects in PD and provides an objective window on relevant clinical features that change post-operatively. It may thus have utilization in clinical trials or investigations into the neural pathways altered by DBS. The lack of change in Tightness supports the notion that DBS does not improve micrographia.

Samuel Beckett on Italian Stages. Intermedial Performances Inspired by his Prose and Poems

My essay focuses on the Italian theatre of the twenty-first century, examining how digital technology revitalises Samuel Beckett’s non-dramatic work. In particular, I want to explore the collision between live performance and digital devices in the staging of the author’s prose and poetry. I will be discussing two case studies: Qual e la parola (2006), and deForma_09 (2009). The former is directed by Roberto Paci Dalo from the company Giardini Pensili and based on twenty-one of Beckett’s poems; the latter is staged under the direction of Michele Sambin from Tam Teatromusica, and it features fragments from the prose fictions Company and Worstward Ho. Both Paci Dalo and Sambin develop an intermedial type of performance, considering Beckett’s words as the core of audio and video processing, which also involves the actors’ bodies. In these projects, new technologies affect both the soundscape and the visual sphere, composing in real-time on both layers. Qual e la parola employs sampling techniques and live-produced music to generate a harmonious sound flow, together with Beckett’s lyrics. Projections of the performers’ figures appear on two gauzes, one positioned on the proscenium area and one on the backdrop. deForma_09 displays a set of sound contents: electronics, spoken words, and noises originated by the actors’ movements on the stage. While four microphones manipulate these elements, Sambin virtually paints on the performers’ silhouettes using a graphics tablet. Keywords: Samuel Beckett; Italian theatre; intermedial performance; digital performance; Giardini Pensili; Tam Teatromusica

Reflections on COVID-19–Induced Online Teaching in Biophysics Courses

Reflections on COVID-19–Induced Online Teaching in Biophysics Courses

APPLICATION OF GRAPHIC EDITORS IN SEARCHING THE COMPOSITION OF PAINTING WORKS

The article examines certain directions in the technological process of creating a composition of an artistic painting that have arisen in the modern creative world. digitalization, affecting not only business, but also cultural life. The introduction of computer technologies and graphic editors, with the help of which many tasks are solved when creating a composition, becomes a good help for a modern artist and is quite acceptable for study and application in the training program for students of artists. In this regard, appears the need for special training of future teachers of painting to work with digital devices, their mastery of methods of working on a computer with graphic tablets and various programs. An artist-teacher who has knowledge in the field of computer technology and the use of specialized software in his arsenal can significantly speed up the process of mastering theoretical, practical and visual material, improving the way of presenting the necessary information, the opportunity to reach a qualitatively new level of education by changing the methods and forms of searching for a compositional solution. Several directions of using "computer art", its advantages and disadvantages are examined, the most acceptable forms of artistic creation using a computer are described, using the experience of artists who turn to them. The analysis is carried out on the examples of the work of teachers and students of the Department of Fine Arts of OGASA, as well as practicing professional artists. This will directly affect the level of training of students and their further competitiveness in the profession market.

Controlling an Industrial Robot Using a Graphic Tablet in Offline and Online Mode.

The article presents the possibility of using a graphics tablet to control an industrial robot. The paper presents elements of software development for offline and online control of a robot. The program for the graphic tablet and the operator interface was developed in C# language in Visual Studio environment, while the program controlling the industrial robot was developed in RAPID language in the RobotStudio environment. Thanks to the development of a digital twin of the real robotic workstation, tests were carried out on the correct functioning of the application in offline mode (without using the real robot). The obtained results were verified in online mode (on a real production station). The developed computer programmes have a modular structure, which makes it possible to easily adapt them to one’s needs. The application allows for changing the parameters of the robot and the parameters of the path drawing. Tests were carried out on the influence of the sampling frequency and the tool diameter on the quality of the reconstructed trajectory of the industrial robot. The results confirmed the correctness of the application. Thanks to the new method of robot programming, it is possible to quickly modify the path by the operator, without the knowledge of robot programming languages. Further research will focus on analyzing the influence of screen resolution and layout scale on the accuracy of trajectory generation.

Ηyper-sinh-Convolutional Neural Network for Early Detection of Parkinson’s Disease from Spiral Drawings

Modern developments in the state-of-the-art open-source activation functions for Convolutional Neural Networks (CNNs) have broadened the selection of benchmark activations for Deep Learning (DL)-aided classification. Nevertheless, achieving discrimination of non-linear input image data in CNN is still not straightforward and it is unclear how such novel activation functions can have translational applications with tangible impact. hyper-sinh, made freely available in TensorFlow and Keras, was demonstrated as a benchmark activation function on five (N=5) datasets in its ground-breaking paper. Measuring the value from deploying this activation in a specific application is pivotal to supply the required evidence of its performance on real-life supervised DL-based image classification tasks. In this study, a CNN was for the first time combined with hypersinh to aid early detection of Parkinson’s Disease (PD) from discriminating pathophysiological patterns extracted from spiral drawings. Thus, the hyper-sinh activation was deployed to maximise the separability of the input features from spiral drawings via automated pattern recognition. We demonstrate the accuracy and reliability of hyper-sinh-CNN to aid early diagnosis of PD, evaluated against other gold standard activation functions, including the recent Quantum ReLU (QReLU) and the modified Quantum ReLU (m-QReLU) that solved the ‘dying ReLU’ problem for the first time in the literature of DL. Two (N=2) benchmark datasets from the database of the Botucatu Medical School, São Paulo State University in Brazil, scaled to be in 28 by 28 pixels as the MNIST benchmark data, were used to discriminate between input image patterns of 158 subjects (53 healthy controls and 105 patients with PD) from spirals drawn on graphics tablets. Overtraining was avoided via early stopping and the models were developed and tested in TensorFlow and Keras (Python 3.6). The supervised model (hyper-sinh-CNN) could detect early Parkinson’s Disease with 81% and 91% classification accuracy from the two datasets respectively (F1-scores: 73% and 91% correspondingly). Furthermore, the model achieved high sensitivity (81% and 91%). Thus, this study validates the application of hyper-sinh to aid real-life supervised DL-based image classification, in particular early diagnosis of PD from spiral drawings.

The influence of modern trends in digital art on the content of training in computer graphics and digital design

The development of digital technologies leads to a variety of pictorial arts. With the advent of computer technology and communication technologies, areas such as computer graphics, computer and digital design, and phenomena such as digital art have emerged. The article analyzes these concepts, which provided an opportunity for further study. Based on the analysis of Internet resources on digital art, the following main trends are identified: virtual art, 3D printing, open source software, art of artificial intelligence, a combination of 2D animation and modern technologies, 3D painting, UX / UI design, game design, concept art and character design. Examples of reflection these tendencies in modern art are given. Given the selected trends, it is shown how they affect the content of training in computer graphics and digital design for students of the educational program "Digital Design" (list of compulsory and optional educational components, the content of educational practice). It is noted that to successfully work with computer graphics, students need to master traditional knowledge of pictorial arts (the concept of composition, color, perspective, proportions, shadows) and the ability to use them to create digital products using computer programs (2D graphic editors and 3D graphics) and digital technology (graphics tablet, personal and personal computer, projection equipment, camera, devices for VR and AR reality, scanner and printer, including 3D scanner and 3D printer).

Мобильные устройства как средство визуализации при дистанционном обучении в медицинском вузе

Objective. The main goal of this work was to describe the concept of a mobile application that supports the functions of an electronic board for mobile devices with a touch screen. Material and methods. The work uses theoretical methods: a review of the literature on the research problem, analysis of publications, as well as an empirical method of observing the distance work of Tyumen State Medical University teachers. Results. The original article reflects the views of the teacher of the medical university on the problem of distance education during the pandemic of the new coronavirus infection and contains a practical proposal for creating a mobile application with which it is possible to facilitate teacher-student interaction during practical sessions conducted using video conferencing systems. The essence of the proposed concept is to synchronize the operation of a personal computer and a mobile device with a touch screen (phone, tablet), as well as a video conferencing system, in which a remote lesson is held, through a mobile application – a virtual board. Such an application turns the touch screen of a mobile device into an analogue of a graphics tablet, on which you can write using any suitable object. In this application the teacher has administrative permission. He can give or restrict access to the virtual clipboard to any student. This will bring the virtual educational process as close as possible to the real one. Conclusion. When implemented thorough of this idea should ensure improve the end result of education. The main disadvantage of this idea is the need for the teacher and students to have both a computer and a mobile device with a touch screen. Also the operation of this application will be difficult in places with low-speed Internet, or when Internet connection is not available.

A systematic approach to diagnose Parkinson’s disease through kinematic features extracted from handwritten drawings

Parkinson’s disease is a slowly progressing neurodegenerative disorder that is not easy to diagnose at the early stages because of delayed symptoms. The most usual ways to diagnose this disease is either by reviewing the medical history of the patient and looking at the computerized tomography scans along with the magnetic resonance imaging by a neurologist or by analyzing the body movements of the patient by the body movement analysts. However, recent research work indicates that Parkinson’s can be effectively diagnosed at an early stage by measuring the changes in handwriting. In this work, the authors have proposed a Parkinson’s disease diagnosis system by analyzing the kinematic features extracted from the handwritten spirals drawn by patients. The publicly available University of California, Irvine Parkinson’s disease spiral drawings using digitized graphics tablet dataset is used in this study. A total of 29 kinematics features are extracted from the dataset. The class imbalance problem in the dataset is handled by the synthetic minority oversampling technique because the dataset is highly imbalanced. Relevant features are selected using the genetic algorithm and mutual information gain feature selection methods. The performance of four classifiers support vector machine, random forest, AdaBoost and XGBoost are analyzed in terms of accuracy, sensitivity, specificity, precision, F-measure, and area under ROC curve. Tenfold cross-validation method is used for validating the results. The combination of mutual information gain feature selection method with AdaBoost classifiers outperforms with 96.02% accuracy.

Use of the Graphic Tablet in the Art and Educational University

This article is discussing application of graphic tablet in the art educational University, by introducing it in design and work with graphical images related to the creation and editing of raster, vector graphics. Sequential drawing of the simplest elements for training the hand’s muscle memory achieved during classes by use of the pen and graphic tablet. The relevance in the application of this device opens up new opportunities in art education when using modern graphic technologies. The main findings observed at the end of the class, where students familiarized themselves with the principles of connection and using the technique of pen (stylus) on the graphics tablet. Students mastered the techniques of drawing from the simplest elements to more complex tasks. The article discusses the practical use of a graphics tablet in modern art education in the context of distant learning.

Development of a Pre-Diagnosis Tool Based on Machine Learning Algorithms on the BHK Test to Improve the Diagnosis of Dysgraphia

Dysgraphia is a writing disorder that affects a significant part of the population, especially school aged children and particularly boys. Nowadays, dysgraphia is insufficiently diagnosed, partly because of the cumbersomeness of the existing tests. This study aims at developing an automated pre-diagnosis tool for dysgraphia allowing a wide screening among children. Indeed, a wider screening of the population would allow a better care for children with handwriting deficits. This study is based on the world's largest known database of handwriting samples and uses supervised learning algorithms (Support Vector Machine). Four graphic tablets and two acquisition software solutions were used, in order to ensure that the tool is not tablet dependent and can be used widely. A total of 580 children from 2nd to 5th grade, among which 122 with dysgraphia, were asked to perform the French version of the BHK test on a graphic tablet. Almost a hundred features were developed from these written tracks. The hyperparameters of the SVM and the most discriminating features between children with and without dysgraphia were selected on the training dataset comprised of 80% of the database (461 children). With these hyperparameters and features, the performances on the test dataset (119 children) were a sensitivity of 91% and a specificity of 81% for the detection of children with dysgraphia. Thus, our tool has an accuracy level similar to a human examiner. Moreover, it is widely usable, because of its independence to the tablet, to the acquisition software and to the age of the children thanks to a careful calibration and the use of a moving z-score calculation.

New HECplus protocol to further improve the accuracy of pan‐endothelial viability measurement

AbstractPurposeThe HEC (Hoechst‐Ethidium‐Calcein) labeling, which we described in 2011, is a simple destructive test unanimously adopted to determine the pan‐endothelial viable endothelial cell density (vECD) using image analysis (e.g. using CorneaJ, ImageJ dedicated plugin). Sometimes, the endothelial surface folded by stromal edema remains difficult to analyze. We present here the HECplus technique, which, with an optimization of image acquisition and analysis, further increases the accuracy of vECD determination, particularly in endothelial folds.Methods10 pairs of corneas stored in organoculture at 31°C were analyzed. The endothelial side was incubated with 4 µM Calcein‐AM, 1 µM Ethidium and 11 µM Hoescht 33342 for 45 min at RT. Fluorescence was acquired in 3 channels first with a macroscope, in 3D with an image stacking of the entire graft then with a microscope after flat mounting. A 2 mm plastic pellet emitting constant fluorescence at 510 nm was imaged at the same time to normalize the images. Only one sharp image was reconstructed in ImageJ from the stacks of images. The final standardized images were then analyzed by CorneaJ (HEC group) and then manually by delimiting all viable surfaces on a graphic tablet (HECplus group)ResultsThe vECD was significantly higher by 8.2 ± 1.9% in the HECplus group versus HEC (2059 ± 127 versus 1989 ± 156 cells/mm2). Endothelial cells died preferentially in the top of the folds and were better preserved in the bottom of the folds. While HEC wrongly considered some folds as dead, HECplus allowed the error to be corrected. The folding pattern was similar between the 2 corneas of the same pair but differed from one donor to another. The normalization of images for calcein showed overall differences in the level of fluorescence between corneas, suggesting differences in metabolic activity.ConclusionsWe recommend applying the HECplus protocol when a very high degree of accuracy is required, for example when comparing storage media.

Using an electromagnetic graphics tablet to analyse manuallycreated graphics

Using an electromagnetic graphics tablet to analyse manuallycreated graphics

OFFLINE YORÙBÁ HANDWRITTEN WORD RECOGNITION USING GEOMETRIC FEATURE EXTRACTION AND SUPPORT VECTOR MACHINE CLASSIFIER

Yorùbá language is one of the three main languages that is been spoken in Nigeria. It is a tonal language that carries an accent on the vowel alphabets. There are twenty-five (25) alphabets in Yorùbá language with one of the alphabets a digraph (GB). Due to the difficulty in typing handwritten Yorùbá documents, there is a need to develop a handwritten recognition system that can convert the handwritten texts to digital format. This study discusses the offline Yorùbá handwritten word recognition system (OYHWR) that recognizes Yorùbá uppercase alphabets. Handwritten characters and words were obtained from different writers using the paint application and M708 graphics tablets. The characters were used for training and the words were used for testing. Pre-processing was done on the images and the geometric features of the images were extracted using zoning and gradient-based feature extraction. Geometric features are the different line types that form a particular character such as the vertical, horizontal, and diagonal lines. The geometric features used are the number of horizontal lines, number of vertical lines, number of right diagonal lines, number of left diagonal lines, total length of all horizontal lines, total length of all vertical lines, total length of all right slanting lines, total length of all left-slanting lines and the area of the skeleton. The characters are divided into 9 zones and gradient feature extraction was used to extract the horizontal and vertical components and geometric features in each zone. The words were fed into the support vector machine classifier and the performance was evaluated based on recognition accuracy. Support vector machine is a two-class classifier, hence a multiclass SVM classifier least square support vector machine (LSSVM) was used for word recognition. The one vs one strategy and RBF kernel were used and the recognition accuracy obtained from the tested words ranges between 66.7%, 83.3%, 85.7%, 87.5%, and 100%. The low recognition rate for some of the words could be as a result of the similarity in the extracted features.

Використання графічного планшету при проведенні синхронних практичних занять з математичного аналізу в умовах дистанційного навчання

Використання графічного планшету при проведенні синхронних практичних занять з математичного аналізу в умовах дистанційного навчання

An Algorithm for the Evolutionary-Fuzzy Generation of on-Line Signature Hybrid Descriptors

Abstract In biometrics, methods which are able to precisely adapt to the biometric features of users are much sought after. They use various methods of artificial intelligence, in particular methods from the group of soft computing. In this paper, we focus on on-line signature verification. Such signatures are complex objects described not only by the shape but also by the dynamics of the signing process. In standard devices used for signature acquisition (with an LCD touch screen) this dynamics may include pen velocity, but sometimes other types of signals are also available, e.g. pen pressure on the screen surface (e.g. in graphic tablets), the angle between the pen and the screen surface, etc. The precision of the on-line signature dynamics processing has been a motivational springboard for developing methods that use signature partitioning. Partitioning uses a well-known principle of decomposing the problem into smaller ones. In this paper, we propose a new partitioning algorithm that uses capabilities of the algorithms based on populations and fuzzy systems. Evolutionary-fuzzy partitioning eliminates the need to average dynamic waveforms in created partitions because it replaces them. Evolutionary separation of partitions results in a better matching of partitions with reference signatures, eliminates dispro-portions between the number of points describing dynamics in partitions, eliminates the impact of random values, separates partitions related to the signing stage and its dynamics (e.g. high and low velocity of signing, where high and low are imprecise-fuzzy concepts). The operation of the presented algorithm has been tested using the well-known BioSecure DS2 database of real dynamic signatures.

Alternative PACS interface devices are well-accepted and may reduce radiologist's musculoskeletal discomfort as compared to keyboard-mouse-recording device.

To evaluate the use of two alternative picture archiving and communication systems (PACS) interface devices (a graphics tablet and a handheld controller) in clinical practice and on task-oriented exercises. Eleven senior radiologists were prospectively evaluated. The participants used the two tested interface devices for 10 working periods each and answered a questionnaire to evaluate the ergonomics of this experience. The prevalence of work-related musculoskeletal discomfort with the standard PACS interface set (mouse-keyboard-recording device) and these two devices was assessed. Exercises evaluating image scrolling and selection, image zooming and panning, image windowing, performing measurements, and reporting were performed with the standard PACS interface set and with the two tested devices. The sitting posture and hand position were evaluated. The general appreciation of the two alternative interface devices was considered to be similar to that of the standard interface set. The ergonomics of the handheld controller was considered to be slightly better than that of the standard interface set. The prevalence of musculoskeletal discomfort was 81%, 45%, and 18% for the standard interface set, graphics tablet, and handheld controller, respectively. With the graphics tablet and the handheld controller in 45% and 60%, respectively, there was a working posture change with respect to the standard interface set. The mean total exercise completion times of both tested devices were 27% higher than that of the standard interface set. Despite the increase in completion time of the task-oriented exercises, the tested devices were well accepted and considered to be more comfortable than the standard set. • Alternative PACS interface devices can be used as a substitute for the standard mouse-keyboard-recording device set with a potential improvement in work ergonomics and a reduction in work-related musculoskeletal discomfort.

Increased error-correction leads to both higher levels of variability and adaptation

In order to intercept moving objects, we need to predict the spatiotemporal features of the motion of both the object and our hand. Our errors can result in updates of these predictions to benefit interceptions in the future (adaptation). Recent studies claim that task-relevant variability in baseline performance can help adapt to perturbations, because initial variability helps explore the spatial demands of the task. In this study, we examined whether this relationship is also found in interception (temporal domain) by looking at the link between the variability of hand-movement speed during baseline trials, and the adaptation to a temporal perturbation. 17 subjects performed an interception task on a graphic tablet with a stylus. A target moved from left to right or vice versa, with varying speed across trials. Participants were instructed to intercept this target with a straight forward movement of their hand. Their movements were represented by a cursor that was displayed on a screen above the tablet. To prevent online corrections we blocked the hand from view, and a part of the cursor's trajectory was occluded. After a baseline phase of 80 trials, a temporal delay of 100 ms was introduced to the cursor representing the hand (adaptation phase: 80 trials). This delay initially caused participants to miss the target, but they quickly accounted for these errors by adapting to most of the delay of the cursor. We found that variability in baseline movement velocity is a good predictor of temporal adaptation (defined as a combination of the rate of change and the asymptotic level of change after a perturbation), with higher variability during baseline being associated with better adaptation. However, cross-correlation results suggest that the increased variability is the result of increased error correction, rather than exploration.