Online Handwriting

Online handwriting analysis focuses on extracting meaningful information from the dynamic process of writing using digital pens and tablets, aiming to improve handwriting recognition, diagnose neurological conditions, and even assess age and mental health. Current research employs various machine learning approaches, including graph neural networks, vision-language models, and ensemble methods, often leveraging multimodal data (combining online and offline handwriting) to enhance accuracy and robustness. This field is significant for its potential applications in assistive technologies for individuals with disabilities, improved human-computer interaction, and objective assessment tools in healthcare, particularly for early detection of age-related decline and mental health issues.