Céline Rémi

The lognormal handwriter: learning, performing and declining

The generation of handwriting is a complex neuromotor skill requiring the interaction of many cognitive processes. It aims at producing a message to be imprinted as an ink trace left on a writing medium. The generated trajectory of the pen tip is made up of strokes superimposed over time. The Kinematic Theory of rapid human movements and its family of lognormal models provide analytical representations of these strokes, often considered as the basic unit of handwriting. This paradigm has not only been experimentally confirmed in numerous predictive and physiologically significant tests but it has also been shown to be the ideal mathematical description for the impulse response of a neuromuscular system. This latter demonstration suggests that the lognormality of the velocity patterns can be interpreted as reflecting the behavior of subjects who are in perfect control of their movements. To illustrate this interpretation, we present a short overview of the main concepts behind the Kinematic Theory and briefly describe how its models can be exploited, using various software tools, to investigate these ideal lognormal behaviors. We emphasize that the parameters extracted during various tasks can be used to analyze some underlying processes associated with their realization. To investigate the operational convergence hypothesis, we report on two original studies. First, we focus on the early steps of the motor learning process as seen as a converging behavior toward the production of more precise lognormal patterns as young children practicing handwriting start to become more fluent writers. Second, we illustrate how aging affects handwriting by pointing out the increasing departure from the ideal lognormal behavior as the control of the fine motricity begins to decline. Overall, the paper highlights this developmental process of merging toward a lognormal behavior with learning, mastering this behavior to succeed in performing a given task, and then gradually deviating from it with aging.

Automatic analysis of the structuring of children's drawings and writing

The aim of this work was to build an objective tool for the detection of graphomotor difficulties involving disorders in the writing of children. We outline some characteristics of layouts, describing the automation level of the graphic activity. We have defined exercises, like copying figures or writing sentences under different conditions that allowed us to measure simple aspects of graphomotor skill up to complex ones. A tool was conceived which was able to automatically extract low-level and high-level primitives. Based on such descriptors, we focus on the analysis of the temporal structuring of two particular drawings. In the final part, we present the method we used to select features that can describe the automation level of the graphic activity and we show that, in most cases, these features allow to discriminate children with academic difficulties.

School level recognition from children's drawings and writing

This paper presents part of the work aiming at building a tool for the detection of graphomotor difficulties involving disorders in the writing of children. We have defined an experimental protocol, containing exercises such as copying figures or writing sentences under different conditions. It allows to measure simple aspects of graphomotor skill up to complex ones. A great number of features were obtained from on-line childrens productions. We focus on the method used to select low-level features that can describe the automation level of graphic activity. It is based on hierarchical clustering of features and sequential forward selection. Every exercise is represented by two relevant features at least. We show that, in most cases, the selected features allow to recognize the school level of children having regular schooling but to discriminate children with scholar difficulties as well.

Personal digital bodyguards for e-security, e-learning and e-health: A prospective survey

Abstract The widespread availability of hand-held devices like tablets, phablets and smart phones, along with their new handwriting digitizing and their increased computing powers, enable these to process the graphomotor dimension and the lognormal trends of human handwriting. By exploiting such capacity, it becomes possible to extend these mobile devices into Personal Digital Bodyguards (PDBs). PDBs will be able to supplement peoples sensitive data protection with signature verification, equipment use security with writer authentication and handwritten CAPTCHAs processing (e-security), and to enhance human-machine interaction performances through words spotting and handwriting recognition (e-recognition). For young children, these tools will turn into interactive toys helping them to learn and master their fine motor control and become better writers. For advanced students they will enable sophisticated systems for (e-learning) and (e-testing). Moreover, PDBs will also be able to provide the user with fine motor control monitoring, which can detect stress, aging and health problems (e-health). This paper presents a prospective survey of various projects dealing with these five e-fields of investigation, focussing on state of the art results and providing directions in research and development, under the theoretical umbrella of the Kinematic Theory of human movements and its Lognormality Principle. From a practical point of view, the concept of lognormality provides a fundamental common thread, an integrative psychophysical standpoint to track the graphomotor problems of signature verification, writer identification, handwriting generation, recognition and learning.

Procedural Analysis of a Sketching Activity: Principles and Applications

The advent of pen-based interfaces has led to the development of many applications concerning the analysis of a drawn shape. But a drawing is not only a shape. It is also all the gestures which constitutes the drawing activity, as well as their planning. Pen-based interfaces give us the possibility to analyze this dimension of sketching. We call this kind of analysis: procedural analysis. In this article, we will show how to identify the privileged drawing procedures of users by identifying a constant pattern despite a huge within-drawer variability in drawing procedures. After stating how to extract this constant pattern, we shall show how we can use those results into a drawing-based user identification method.

Analyse procédurale: un nouveau paradigme pour l'analyse de tracés manuscrits

In this paper, we present a new axis concerning a possible use of pen based HCI. It is common to use those interfaces for applications concerning visuo-spatial treatments such as shape recognition. But we believe that the possibilities offered by those interface allow one to consider other kind of treatments focusing not on the shape but on analyzing drawers process during the sketching activity. Those approaches, that we call ≪ Procedural analysis ≫, are almost nonexistent. In this article we will detail what is a procedural analysis and we will show some possible uses of those kinds of methods.