Abstract
Cervical myelopathy (CM) is a progressive spinal disorder affecting hand function. We developed two machine learning-based screening methods: one using tablet drawings and another using smartphone-captured paper drawings. In the tablet method, users trace spiral, square, and triangular figures with a stylus, which a convolutional neural network classifies with 95% sensitivity and 85% specificity, exceeding conventional examinations. The smartphone method captures paper drawings, enabling screening without specialized equipment. Together, these approaches provide accessible and reliable CM screening in clinical and non-clinical settings.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of MUM 2025 - The 24th International Conference on Mobile and Ubiquitous Multimedia |
| Editors | Salvatore Sorce, Passant Elagroudy, Mohamed Khamis |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 486-488 |
| Number of pages | 3 |
| ISBN (Electronic) | 9798400720154 |
| DOIs | |
| Publication status | Published - 2025 Nov 30 |
| Event | 24th International Conference on Mobile and Ubiquitous Multimedia, MUM 2025 - Enna, Italy Duration: 2025 Dec 1 → 2025 Dec 4 |
Publication series
| Name | Proceedings of MUM 2025 - The 24th International Conference on Mobile and Ubiquitous Multimedia |
|---|
Conference
| Conference | 24th International Conference on Mobile and Ubiquitous Multimedia, MUM 2025 |
|---|---|
| Country/Territory | Italy |
| City | Enna |
| Period | 25/12/1 → 25/12/4 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cervical Myelopathy
- Mobile Health
- Screening
- Smartphone
- Tablet
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Human-Computer Interaction
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