Graphonomics in Human Body Movement. Bridging Research and Practice from Motor Control to Handwriting Analysis and Recognition (Lecture Notes in Computer Science)

Preface
Organization
Contents
Handwriting Learning and Development
A Short Review on Graphonometric Evaluation Tools in Children
	1 Introduction
	2 Bibliometric Analysis
	3 Participants
	4 Methods of Evaluation of the Graphonometric State in Children
		4.1 Objective Evaluation Methods
		4.2 Subjective Evaluation Methods
		4.3 Objective and Subjective Evaluation Methods
	5 Discussion and Conclusion
	References
Assessment of Developmental Dysgraphia Utilising a Display Tablet
	1 Introduction
	2 Materials and Methods
		2.1 Dataset
		2.2 Feature Extraction
		2.3 Statistical Analysis and Machine Learning
	3 Results
	4 Discussion
	5 Conclusion
	References
Analysis of Eye Movements in Children with Developmental Coordination Disorder During a Handwriting Copy Task
	1 Introduction
	2 Materials and Methods
		2.1 Participants
		2.2 The Experiment
	3 Results
		3.1 Eye Movements During the Exploration Phase.
		3.2 Eye Movements During the BHK Copying Phase
	4 Discussion
	References
Handwriting Analysis
On the Analysis of Saturated Pressure to Detect Fatigue
	1 Introduction
		1.1 State of the Art
	2 Methodology
		2.1 Database
		2.2 Feature Extraction
	3 Experimental Results
	4 Conclusions
	References
Handwriting for Education
IntuiSketch, a Pen-Based Tutoring System for Anatomy Sketch Learning
	1 Introduction
	2 Recognition Engine
		2.1 CD-CMG Principles
		2.2 Incremental Classifier Evolve
	3 IntuiSketch Architecture
		3.1 Architecture Founding Principles
		3.2 Adaptation of the Architecture for Complex Sketches
	4 Interaction Between Tutoring and Pattern Recognition
		4.1 Domain Module: Knowledge Graph Construction
		4.2 Learner Module: Matching and Feedback Generation
	5 Qualitative Evaluation
	6 Conclusion and Perspectives
	References
Towards Visuo-Structural Handwriting Evaluation Based on Graph Matching
	1 Introduction
	2 Dataset Used for This Study
		2.1 Tool Used for Online Acquisition and Human Evaluation of Images
		2.2 Nature and Context of the Image Acquisition
		2.3 Description of the Ground Truth
	3 Methods
		3.1 Graph-Based Approach Principle
		3.2 Classification of Graphs Using Similarity Measures
		3.3 Clustering of Graphs Using Similarity Measures
	4 Experimental Evaluation
		4.1 Parameter Optimisation
		4.2 Results with Classification
		4.3 Results with Clustering
	5 Conclusion
	References
Copilotr@ce Put to the Crowdsourcing Test
	1 Introduction
	2 Presentation of Copilotr@ce and Its First Uses
	3 Application
		3.1 First Crowdsourcing Experience Initiated with Copilotr@ce
		3.2 Provisional Assessment of this Copilotr@ce Crowdsourcing Experiment
		3.3 Potential Application of Dataset Built from this Crowdsourcing Experiment
	4 Discussion
	5 Conclusion
	References
Handwriting for Neurodegenerative Disorders
A Machine Learning Approach to Analyze the Effects of Alzheimer\'s Disease on Handwriting Through Lognormal Features
	1 Introduction
	2 The Sigma-Lognormal Model
	3 Description
		3.1 Data Collection
		3.2 Tasks
		3.3 Feature Engineering
	4 Experimental Phase
		4.1 Workflow
		4.2 Results
		4.3 Feature Findings
	5 Conclusions and Future Work
	References
Feature Evaluation in Handwriting Analysis for Alzheimer\'s Disease Using Bayesian Network
	1 Introduction
	2 Acquisition Protocol and Features
	3 Bayesian Network for Feature Evaluation
	4 Experimental Findings
	5 Conclusions
	References
I Can\'t Believe It\'s Not Better: In-air Movement for Alzheimer Handwriting Synthetic Generation
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Generator
		3.2 Discriminator
	4 Dataset
	5 Experiments
	6 Results
	7 Discussion
	8 Conclusion
	References
Handwritten Historical Documents
The Neglected Role of GUI in Performance Evaluation of AI-Based Transcription Tools for Handwritten Documents
	1 Introduction
	2 The Transcription Process
	3 Experimental Results
		3.1 Datasets
		3.2 KWS System
		3.3 KWS Performance
		3.4 How GUI Times Affects the Time Gain
	4 Discussion
	5 Conclusions
	References
Estimating the Optimal Training Set Size of Keyword Spotting for Historical Handwritten Document Transcription
	1 Introduction
	2 Releated Works
	3 The Transcription Process
	4 Experimentation Details
		4.1 Datasets
		4.2 KWS System
		4.3 Temporal Gain
	5 Results
	6 Discussion and Conclusion
	References
A Digital Analysis of Mozart’s F-Clefs
	1 Introduction
	2 Methodology
		2.1 Preprocessing
		2.2 Feature Extraction
		2.3 Method of Analysis
	3 Analysis
	4 Conclusion
	References
Special Session on Movement Variability
Methods for Analyzing Movement Variability
	1 Introduction
		1.1 Definition
		1.2 Human Movement Variability
		1.3 Dynamical Systems Theory
	2 Non-linear Methods
		2.1 Fractal Dimension
		2.2 Sample Entropy
		2.3 Lyapunov Exponent
		2.4 Recurrence Quantification Analysis
		2.5 Handwriting and Nonlinear analysis
		2.6 Virtual Reality and Movement
	3 Final Considerations
	References
Special Session on Lognormality
Lognormality: An Open Window on Neuromotor Control
	1 Introduction
	2 The Lognormality Principle: Theory and Overview of Some Applications
		2.1 Context
		2.2 The Lognormality in practice
		2.3 Workshop Program
	3 AGING
		3.1 Remote Monitoring of Stroke Patients via 3D Kinematics and Artificial Intelligence
		3.2 Kinematic Signature in People with Parkinson’s and Psoriatic Arthritis: Potential of the Sigma-Lognormal Approach
		3.3 Contribution of Lognormality in the Identification of Kinematic Biomarkers in the Identification and Early Differential Diagnosis of Parkinson’s Disease
	4 Performances
		4.1 Deep Reinforcement Learning for ECG Modelling Using Lognormals
		4.2 Kinematic Theory, Muscle Fatigue and Optimality: Contribution to the Biomechanics of the Upper limb
		4.3 Objective Analysis of Surgical Performance thanks to a Simulator Augmented by Artificial Vision
		4.4 Kinematic Reconstruction of Static Calligraphic Traces from Curvilinear Features
	5 Techniques
		5.1 Separation Algorithm and Evaluation Applied to the Delta-Lognormal Model
		5.2 Analysis of Three-Dimensional Movements with the Sigma-Lognormal Model
		5.3 Comparison of Symbolic and Connectionist Algorithms to Correlate the Age of Healthy Children with Sigma-Lognormal Neuromotor Parameters
	6 Childhood
		6.1 Interest of Kinematic Theory and its Lognormal Models in Assessing Graphomotor Skills in Kindergarten and First Grade Students in France and in Québec
		6.2 The use of the Lognormality Principle for the Characterization and Analysis of Graphomotor Behaviours Involving Young Learners in a School Context
		6.3 Lognormality in Children with Mild Traumatic Brain Injury: a Pilot Study
		6.4 Kinematic Analyses of Rapid Pencil Strokes Produced by Children with ADHD
		6.5 Screening for Developmental Problems in Preterm Born Children: Utility of the Pen Stroke Test During the Preschool Period
		6.6 Exploring the Benefits of Virtual Reality Lognormality Analysis for Diagnosing ADHD in Children
	7 Conclusion
	References
Author Index