Haptic System for Handwriting Training and Classification
Nowadays, handwriting still plays an important role in our lives, even though we live in a progressively more digital era. Therefore, losing the ability to write, whether because of physical or psychological complications, can become a huge handicap. The system described herein aims, in a first stage, to enable handwriting training through haptic guidance. The implementation was performed in Visual Studio and with the use of OpenHaptics toolkit. The second stage consists in character classification, written using a haptic joystick. The pre-eminent procedure for digit classification consists in the use of Histogram of Oriented Gradients coupled with a multiclass Support Vector Machine (HOG-SVM) whereas for letters the strategy involves using a Convolutional Neural Network (CNN).
Authors
- Manuel Crisóstomo (ORCID: https://orcid.org/0000-0002-3240-7564)
- João Paulo Ferreira (ORCID: https://orcid.org/0000-0003-0143-9421)
- A. Paulo Coimbra (ORCID: https://orcid.org/0000-0003-3780-2405)
Institutions
- Escola Superior de Tecnologia da Saúde de Coimbra (PT)
- Institute for Systems Engineering and Computers (PT)
- University of Coimbra (PT)
Publication Details
- Published
- 2024-12-12
- DOI
- https://doi.org/10.1109/icarcv63323.2024.10821540
- Primary Topic
- Hand Gesture Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fundação para a Ciência e a Tecnologia