# Online handwriting, signature and touch dynamics: tasks and potential applications in the field of security and health

arXiv: https://arxiv.org/abs/2202.12693 · HTML: https://mlsanity.com/paper/2202.12693/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 118 references that are in the map.
- First posted on arXiv 24 Feb 2022.

## Builds on (most cited first, 4 of 4)

- [DeepWriterID: An End-to-end Online Text-independent Writer Identification System](https://mlsanity.com/paper/1508.04945/) (2015)
- [Computer keyboard interaction as an indicator of early Parkinson's disease](https://mlsanity.com/paper/1604.08620/) (2016)
- [EMOTHAW: A novel database for emotional state recognition from handwriting](https://mlsanity.com/paper/2202.12245/) (2022)
- [A comparative study of in-air trajectories at short and long distances in online handwriting](https://mlsanity.com/paper/2202.12237/) (2022)

## Built on by (most cited first, 7 of 7)

- [On the use of first and second derivative approximations for biometric online signature recognition](https://mlsanity.com/paper/2406.00512/) (2024)
- [Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties](https://mlsanity.com/paper/2301.08534/) (2023)
- [Online Signature Recognition: A Biologically Inspired Feature Vector Splitting Approach](https://mlsanity.com/paper/2405.12556/) (2024)
- [Graphomotor and Handwriting Disabilities Rating Scale (GHDRS):towards complex and objective assessment](https://mlsanity.com/paper/2405.17886/) (2024)
- [On the analysis of saturated pressure to detect fatigue](https://mlsanity.com/paper/2411.04128/) (2024)
- [Contrastive Masked Autoencoders for Character-Level Open-Set Writer Identification](https://mlsanity.com/paper/2501.11895/) (2025)
- [BoundInk: Boundary-Aware Online Handwriting Generation](https://mlsanity.com/paper/2604.02103/) (2026)

## Abstract (arXiv)

Background: An advantageous property of behavioural signals ,e.g. handwriting, in contrast to morphological ones, such as iris, fingerprint, hand geometry, etc., is the possibility to ask a user for a very rich amount of different tasks. Methods: This article summarises recent findings and applications of different handwriting and drawing tasks in the field of security and health. More specifically, it is focused on on-line handwriting and hand-based interaction, i.e. signals that utilise a digitizing device (specific devoted or general-purpose tablet/smartphone) during the realization of the tasks. Such devices permit the acquisition of on-surface dynamics as well as in-air movements in time, thus providing complex and richer information when compared to the conventional pen and paper method. Conclusions: Although the scientific literature reports a wide range of tasks and applications, in this paper, we summarize only those providing competitive results (e.g. in terms of discrimination power) and having a significant impact in the field.