Computer Vision and EMG-Based Handwriting Analysis for Classification in Parkinson's Disease

Handwriting analysis represents an important research area in different fields. From forensic science to graphology, the automatic dynamic and static analyses of handwriting tasks allow researchers to attribute the paternity of a signature to a specific person or to infer medical and psychological patients’ conditions. An emerging research field for exploiting handwriting analysis results is the one related to Neurodegenerative Diseases (NDs). Patients suffering from a ND are characterized by an abnormal handwriting activity since they have difficulties in motor coordination and a decline in cognition.

[1]  Vitoantonio Bevilacqua Three-dimensional virtual colonoscopy for automatic polyps detection by artificial neural network approach: New tests on an enlarged cohort of polyps , 2013, Neurocomputing.

[2]  G. Stelmach,et al.  Parkinsons disease and the control of size and speed in handwriting , 1999, Neuropsychologia.

[3]  Pille Taba,et al.  Handwriting speed and size in individuals with Parkinson’s disease compared to healthy controls: the possible effect of cueing , 2014 .

[4]  R. Schwab,et al.  Micrographia in Parkinson's disease. , 1972, Journal of the neurological sciences.

[5]  Vitoantonio Bevilacqua,et al.  An Optimized Feed-forward Artificial Neural Network Topology to Support Radiologists in Breast Lesions Classification , 2016, GECCO.

[6]  Vitoantonio Bevilacqua,et al.  A Novel Multi-Objective Genetic Algorithm Approach to Artificial Neural Network Topology Optimisation: The Breast Cancer Classification Problem , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[7]  Gang Wang,et al.  Feature selection with conditional mutual information maximin in text categorization , 2004, CIKM '04.

[8]  Antonio Frisoli,et al.  An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation , 2015, IEEE Transactions on Haptics.

[9]  G E Stelmach,et al.  Micrographia in Parkinson's disease. , 1995, Neuroreport.

[10]  Rüdiger W. Brause,et al.  Handwriting Analysis for Diagnosis and Prognosis of Parkinson's Disease , 2006, ISBMDA.

[11]  B Conrad,et al.  Changes in handwriting resulting from bilateral high‐frequency stimulation of the subthalamic nucleus in Parkinson's disease , 1999, Movement disorders : official journal of the Movement Disorder Society.

[12]  Sonia Kandel,et al.  Handwriting in patients with Parkinson disease: effect of L-dopa and stimulation of the sub-thalamic nucleus on motor anticipation. , 2011, Human movement science.

[13]  Zdenek Smekal,et al.  Prediction potential of different handwriting tasks for diagnosis of Parkinson's , 2013, 2013 E-Health and Bioengineering Conference (EHB).

[14]  George E. Stelmach,et al.  Prehension movements in Parkinson's disease , 1992 .

[15]  Rifat Sipahi,et al.  Toward Monitoring Parkinson's Through Analysis of Static Handwriting Samples: A Quantitative Analytical Framework , 2017, IEEE Journal of Biomedical and Health Informatics.

[16]  A. Wing,et al.  Agraphia and micrographia: clinical manifestations of motor programming and performance disorders. , 1983, Acta psychologica.

[17]  G E Stelmach,et al.  Discrete and dynamic scaling of the size of continuous graphic movements of parkinsonian patients and elderly controls , 2003, Journal of neurology, neurosurgery, and psychiatry.

[18]  Denis Alamargot,et al.  Does handwriting on a tablet screen affect students' graphomotor execution? A comparison between Grades Two and Nine. , 2015, Human movement science.

[19]  G E Stelmach,et al.  Parkinson’s disease patients undershoot target size in handwriting and similar tasks , 2003, Journal of neurology, neurosurgery, and psychiatry.

[20]  E. Carmeli,et al.  The aging hand. , 2003, The journals of gerontology. Series A, Biological sciences and medical sciences.

[21]  G. Stelmach,et al.  Movement accuracy constraints in Parkinson’s disease patients , 2000, Neuropsychologia.

[22]  G. Stelmach,et al.  Parkinsonian Patients Reduce Their Stroke Size with Increased Processing Demands , 2001, Brain and Cognition.

[23]  G. Stelmach,et al.  Adaptation of handwriting size under distorted visual feedback in patients with Parkinson's disease and elderly and young controls , 2002, Journal of neurology, neurosurgery, and psychiatry.

[24]  J G Nutt,et al.  Determinants of tapping speed in normal control subjects and subjects with Parkinson's disease: Differing effects of brief and continued practice , 2000, Movement disorders : official journal of the Movement Disorder Society.

[25]  Andrew M. Gordon,et al.  Task-Dependent Deficits during Object Release in Parkinson's Disease , 1998, Experimental Neurology.

[26]  M. Samuel,et al.  Handwriting as an objective tool for Parkinson’s disease diagnosis , 2013, Journal of Neurology.

[27]  Antonio Frisoli,et al.  An emg-based robotic hand exoskeleton for bilateral training of grasp , 2013, 2013 World Haptics Conference (WHC).

[28]  N Mai,et al.  Computational analysis of open loop handwriting movements in Parkinson's disease: A rapid method to detect dopamimetic effects , 1996, Movement disorders : official journal of the Movement Disorder Society.

[29]  G. Stelmach,et al.  Control of stroke size, peak acceleration, and stroke duration in Parkinsonian handwriting , 1991 .

[30]  T. Flash,et al.  Kinematic analysis of upper limb trajectories in Parkinson's disease , 1992, Experimental Neurology.

[31]  Andrew P. Bradley,et al.  The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..

[32]  John P. Wann,et al.  The control of pen pressure in handwriting: A subtle point , 1991 .

[33]  G E Stelmach,et al.  Stability of reach-to-grasp movement patterns in Parkinson's disease. , 1997, Brain : a journal of neurology.

[34]  John G. Nutt,et al.  Diagnosis and Initial Management of Parkinson's Disease , 2005 .