Machine learning approach for bipolar disorder analysis and recognition based on handwriting digital images
نویسندگان
1 Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran
2 Department of Biomedical Engineering, University of Houston, USA
3 Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran
4 Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran
doi
10.22060/ajmc.2024.22576.1176چکیده
In some cases, handwriting is a manifestation of the human mind, and it can reveal various psychological characteristics and mental disorders. Among these disorders, bipolar disorder is a well-known and widely studied condition in cognitive science and psychotherapy, and it can be detected in handwriting. In this research, we applied image processing techniques to analyze the handwriting characteristics of people with bipolar disorder based on their responses to a survey. We also proposed a machine learning model that can classify whether a person has bipolar disorder or not by using their handwriting as an input.
