The Importance of Pen Motion Pattern Groups for Semi-Automatic Classification of Handwriting into Mental Workload Classes

In this paper, we introduce the pen motion pattern groups (PMPGs) and their contribution to the classification of handwriting into cognitive mental workload classes. We demonstrate the importance of PMPGs by providing an efficient semi-automatic machine learning-based classification framework that distinguishes between handwritten texts written by the same person under different mental workloads. Our evaluation framework is...