Published January 19, 2025
| Version v1
Dataset
Open
Simulated_Drifted_Dataset
Authors/Creators
Description
The curate dataset comprises 174 tabular entries, each representing handwriting data generated from 25 neuroscience-informed tasks. These tasks are categorized into three groups: Memory and Dictation (M), Graphic (G), and Copy (C). Each task contributes 18 distinct handwriting features. This structure results in a total of 450 tabular features (25 tasks × 18 features) per sample, offering a comprehensive and structured dataset for Alzheimer’s research. This tabular format 174 x 450 (provided in .csv file format) facilitates detailed analysis and supports the application of machine learning techniques to study effect data drift to determine cognitive and motor impairments
Files
Simulated_Drifted_Dataset-main.zip
Additional details
Identifiers
Related works
- Describes
- Dataset: 10.5281/zenodo.14689791 (DOI)
Dates
- Submitted
-
2025-01-19
References
- Mitra, U., & Rehman, S. U. (2024). ML-Powered Handwriting Analysis for Early Detection of Alzheimer's Disease. IEEE Access