Ariella Richardson, Sarit Kraus , Patrice L. Weiss , Sara Rosenblum
In this paper we present COACH - a Cumulative Online Algorithm for Classification of Handwriting deficiencies. A description of our algorithm along with a performance evaluation of COACH on real data is provided. COACH is an innovative algorithm designed for building an online handwriting evaluation tool to be used for classifying and remediating handwriting deficiencies. COACH adapts learning and data mining techniques from AI to handwriting deficiency classification in an innovative fashion. Until now handwriting classification has been performed manually by trained therapists causing expensive and subjective evaluation. This application lowers the cost of evaluation, increases objectiveness, and enables repeated testing that can accompany therapy. COACH is evaluated on real data obtained from children with poor handwriting using a digitizer tablet. Results show that COACH manages to successfully differentiate between poor to proficient handwriting. Differentiation is obtained even after using data from only a few words. These results prove that COACH is a promising emerging application for online evaluation.
Subjects: 1.5 Diagnosis; 12. Machine Learning and Discovery
Submitted: Mar 19, 2008