Robust remote detection of depressive tendency based on keystroke dynamics and behavioural characteristics

• Published in: Scientific reports Vol. 14; no. 1; pp. 28025 - 13
• Main Authors: Fadul, Ruba, AlShehhi, Aamna, Hadjileontiadis, Leontios
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.11.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1305; 631/114/1386; 692/53/2421; 692/699/476/1414; Depression disease; Detection; Humanities and Social Sciences; Interactive computer systems; Keystroke dynamics; Machine learning; Mental depression; Mental disorders; multidisciplinary; Remote screening; Science; Science (multidisciplinary); Smartphones; Typing; Remote screening; Typing; Detection; Depression disease; Keystroke dynamics; Machine learning

Depressive Disorder (DD) is a leading cause of disability worldwide. Screening tools for detecting DD symptoms are essential for monitoring and efficient managing. Remarkably, individuals’ kinetic activities, including their interaction with touchscreen smartphones, can be a proxy for their mental s...