aphasia-populations

Processing of AphasiaBank's populations with and without non-fluent aphasia

Files:

• descriptive_data.py: generates descriptive statistics and histograms for outcome datasets. Outputs files into Plots directory.
• preprocessing.r: Filters each CSV file to obtain each population. Outputs CSV files into the 'Output CSV' directory.

Directories:

• Output CSV: Stores four CSV files for filtered populations that are created with preprocessing.R
• Removed Data: Stores 38 CSV files for removed data with preprocessing.R
• Plots: Stores histograms, scatter matricies, distribution charts, and descriptive data output from descriptive_data.py.

Requirements:

• R-3.3.2 or higher. Download at: http://cran.r-project.org
• python 3.6 or higher. Download at: https://www.python.org/downloads/

The following files can be downloaded from the AphasiaBank Database:

• aphasiaDemographics: Demographic data for individuals with aphasia
• aphasiaNoComp: AphasiaBank CHAT output for all aphasia participants in percentages
• aphasiaNoCompNum: AphasiaBank CHAT output for all aphasia participants in raw numbers
• aphasiaTestResults: Testing data for individuals with aphasia
• controlDemographics: Demographic data for individuals without aphasia
• controlNoComp: AphasiaBank CHAT output for individuals without aphasia
• controlNoCompNum: AphasiaBank CHAT output for individuals without aphasia, in raw numbers

Usage:

1. Run preprocessing.R
2. Run descriptive_data.py

Citation:

Feel free to use this code and alter it to fit your research needs. If you reference this content, please cite one of the following:

Garcia, P. 2017. Aphasia Populations. Github repository. https://github.com/paulaux/aphasia-populations

Garcia, P. 2017. Distribution of Language Measures among Individuals with and without Non-fluent Aphasia. In Proceedings of the 10th International Conference on Pervasive Technologies Related to Assistive Environments (PETRA'17). ACM Press, New York, NY, 252-253. DOI:https://doi.org/10.1145/3056540.3076214.