Discriminative Power of Handwriting and Drawing Features in Depression
Metadatos
Mostrar el registro completo del ítemAutor
Greco, Claudia; Raimo, Gennaro; Amorese, Terry; Cuciniello, Marialucia; McConvey, Gavin; Cordasco, Gennaro; Faundez Zanuy, Marcos; Vinciarelli, Alessandro; Callejas Carrión, Zoraida; Esposito, AnnaEditorial
World Scientic
Materia
Depression Handwriting On-line analysis
Fecha
2023-11-24Referencia bibliográfica
Greco, Claudia, et al. "Discriminative Power of Handwriting and Drawing Features in Depression." International Journal of Neural Systems (2023): 2350069-2350069 [10.1142/S0129065723500697]
Patrocinador
European Union Horizon 2020 research and innovation program under grant agreement No. 769872 (EMPATHIC); European Union Horizon 2020 research and innovation program under grant agreement No. 823907 (MENHIR); Project SIROBOTICS that received funding from Ministero dell'Istruzione, dell'Università, e della Ricerca (MIUR), PNR 2015- 2020, D.D. 1735/2017; Project ANDROIDS that received funding from Università della Campania \Luigi Vanvitelli" inside the program V:ALERE 2019, funded with D.R. 906/2019; Project SALICE that received funding from Università della Campania \Luigi Vanvitelli" inside the program Giovani Ricercatori (DR 509/2022), funded with DR 834/2022Resumen
This study contributes knowledge on the detection of depression through handwriting/drawing features, to identify quantitative and noninvasive indicators of the disorder for implementing algorithms for its automatic detection. For this purpose, an original online approach was adopted to provide a dynamic evaluation of handwriting/drawing performance of healthy participants with no history of any psychiatric disorders (n=28), and patients with a clinical diagnosis of depression (n=27). Both groups were asked to complete seven tasks requiring either the writing or drawing on a paper while five handwriting/drawing features’ categories (i.e. pressure on the paper, time, ductus, space among characters, and pen inclination) were recorded by using a digitalized tablet. The collected records were statistically analyzed. Results showed that, except for pressure, all the considered features, successfully discriminate between depressed and nondepressed subjects. In addition, it was observed that depression affects different writing/drawing functionalities. These findings suggest the adoption of writing/drawing tasks in the clinical practice as tools to support the current depression detection methods. This would have important repercussions on reducing the diagnostic times and treatment formulation.