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...
Avis, G., D'Adda, F., Chieregato, D., Guarnieri, E., Meliante, M., Pierotti, A., et al. (2024). A Neural Network for Automatic Handwriting Extraction and Recognition in Psychodiagnostic Questionnaires. In International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings (pp.140-151). Science and Technology Publications, Lda [10.5220/0012587600003699].
A Neural Network for Automatic Handwriting Extraction and Recognition in Psychodiagnostic Questionnaires
Avis G. R.;D'Adda F.;Chieregato D.;Guarnieri E.;Pierotti A. P.;Cremaschi M.
2024
Abstract
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...I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.