SYSTEM TO DETECT HANDWRITING DISABILITY AND METHOD THEREOF
- Sangeetha Chandran
- Dr. Santhoshkumar M.B.
The present invention relates to the field of computer science, inclusive education, and artificial intelligence technology, in particular to dysgraphia or handwriting disability detection based on language biomarkers in the Indian language system. The system (102) works as a screening, intervention, and recommendation model in orthographically complex languages based on biomarkers. The system (102) collects handwriting samples (304) and handwriting parameters (306). The system (102) further acquires at least heartbeat, blood pressure, and brain activity data pertaining to handwriting activities (306). Further, the system (102) processes the collected samples and data to identify biomarkers that indicate some biological state or condition. In the present disclosure, the biomarkers are introduced with natural language processing and machine learning for detecting dysgraphia. Upon detection of dysgraphia, the system (102) provides feedback (318) to improve the handwriting of the user (104).