A Neural Network for Automatic Handwriting Extraction and Recognition in Psychodiagnostic Questionnaires
Giulia Rosemary Avis, Fabio D’Adda, David Chieregato, Elia Guarnieri, Maria Meliante, Andrea Primo Pierotti, Marco Cremaschi · 2024
This paper presents PANTHER, a neural network model for automatic handwriting extraction and recognition in psychodiagnostic questionnaires. Psychodiagnostic tools are essential for assessing and monitoring mental health conditions, but they often rely on pen-and-paper administration, which poses several challenges for data collection and analysis. PANTHER aims to address this problem by using a convolutional neural network to classify scanned questionnaires into their respective types and extract the patient’s responses from the handwritten annotations. The model is trained and evaluated on a dataset of five questionnaires commonly used in psychological and psychiatric settings, achieving high accuracy and similarity scores. The paper also describes the creation of an open-source library based on PANTHER, which can be integrated into a digital platform for delivering psychological services. This paper contributes to the field of computer vision and psychological assessment by providin...