|
1 | 1 | # Graphomotor Study Toolkit |
2 | 2 |
|
| 3 | +A Python toolkit for analysis of graphomotor data collected via Curious. |
| 4 | + |
| 5 | +[](https://doi.org/10.5281/zenodo.15800191) |
| 6 | + |
3 | 7 | [](https://github.com/childmindresearch/graphomotor/actions/workflows/test.yaml?query=branch%3Amain) |
4 | 8 | [](https://codecov.io/gh/childmindresearch/graphomotor) |
5 | 9 | [](https://github.com/astral-sh/ruff) |
6 | 10 |  |
7 | 11 | [](https://github.com/childmindresearch/graphomotor/blob/main/LICENSE) |
8 | | -[](https://childmindresearch.github.io/graphomotor) |
| 12 | +[](https://childmindresearch.github.io/graphomotor) |
| 13 | + |
| 14 | +Welcome to `graphomotor`, a specialized Python library for analyzing graphomotor data collected via [Curious](https://www.gettingcurious.com/). This toolkit provides comprehensive tools for processing, analyzing, and visualizing data from various graphomotor assessment tasks including spiral drawing, trails making, alphabetic writing, digit symbol substitution, and the Rey-Osterrieth Complex Figure Test. |
9 | 15 |
|
10 | | -A Python toolkit for the analysis of Graphomotor study. |
| 16 | +## Development Progress |
11 | 17 |
|
12 | | -## Progress |
| 18 | +⚠️ **This package is under active development.** Currently, the focus is on the Spiral task. After finalizing feature extraction, the next steps will involve implementing both preprocessing and visualization for this task. Once these parts are in place, we plan to extend support to other tasks. |
13 | 19 |
|
14 | | -| Task name | Preprocessing | Feature extraction | Visualization | |
| 20 | +| Task | Preprocessing | Feature Extraction | Visualization | |
15 | 21 | | :--- | :---: | :---: | :---: | |
16 | | -| Spiral |  |  |  | |
17 | | -| Rey-Osterrieth Complex Figure |  |  |  | |
18 | | -| Alphabetic Writing | |  |  | |
19 | | -| Digit Symbol Substitute | |  |  | |
20 | | -| Trails Making |  |  |  | |
| 22 | +| Spiral |  |  |  | |
| 23 | +| Rey-Osterrieth Complex Figure |  |  |  | |
| 24 | +| Alphabetic Writing |  |  |  | |
| 25 | +| Digit Symbol Substitution |  |  |  | |
| 26 | +| Trails Making |  |  |  | |
| 27 | + |
| 28 | +## Data Format Requirements |
| 29 | + |
| 30 | +⚠️ **This implementation requires data to adhere to a specific format matching the standard output from [Curious drawing responses](https://mindlogger.atlassian.net/servicedesk/customer/portal/3/article/859242501).** |
| 31 | + |
| 32 | +When exporting drawing data from Curious, you typically receive the following files: |
| 33 | + |
| 34 | +- **report.csv**: Contains the participants' actual responses. |
| 35 | +- **activity_user_journey.csv**: Logs the entire journey through the activity, including button actions like "Next", "Skip", "Back", and "Undo", regardless of whether a response was provided. |
| 36 | +- **drawing-responses-{date}.zip**: A ZIP archive with raw drawing response CSV files for each participant (e.g., `drawing-responses-Mon May 29 2023.zip`). |
| 37 | +- **media-responses-{date}.zip**: A ZIP archive containing SVG files for the drawing responses (e.g., `media-responses-Mon May 29 2023.zip`). |
| 38 | +- **trails-responses-{date}.zip**: A ZIP archive with raw trail making response CSV files (if there are any) for each participant (e.g., `trails-responses-Mon May 29 2023.zip`). |
| 39 | + |
| 40 | +For Spiral tasks, the toolkit uses only the CSV files from the drawing responses ZIP. Support for additional tasks will be added in future releases. |
| 41 | + |
| 42 | +### File Naming Convention |
| 43 | + |
| 44 | +Your spiral data files must follow this naming convention: |
| 45 | + |
| 46 | +```text |
| 47 | +[5123456]a7f3b2e9-d4c8-f1a6-e5b9-c2d7f8a3e6b4-spiral_trace1_Dom.csv |
| 48 | +``` |
| 49 | + |
| 50 | +Where: |
| 51 | + |
| 52 | +- **Participant ID**: Must be enclosed in brackets `[]` and be a 7-digit number starting with `5` (e.g., `[5123456]`) that matches the `target_secret_id` column in the **report.csv** file. |
| 53 | +- **Activity Submission ID**: Must be a 32-character hexadecimal string (e.g., `18f2-45ea-a1e4-2334e07cc706`) that matches the `id` column in the **report.csv** file. |
| 54 | +- **Task**: Must be one of the following that matches the `item` column in the **report.csv** file: |
| 55 | + - `spiral_trace1_Dom` through `spiral_trace5_Dom` (dominant hand tracing tasks) |
| 56 | + - `spiral_trace1_NonDom` through `spiral_trace5_NonDom` (non-dominant hand tracing tasks) |
| 57 | + - `spiral_recall1_Dom` through `spiral_recall3_Dom` (dominant hand recall tasks) |
| 58 | + - `spiral_recall1_NonDom` through `spiral_recall3_NonDom` (non-dominant hand recall tasks) |
| 59 | + |
| 60 | +### Data Format |
| 61 | + |
| 62 | +Your spiral data CSV file must contain the following columns: |
| 63 | + |
| 64 | +```text |
| 65 | +line_number, x, y, UTC_Timestamp, seconds, epoch_time_in_seconds_start |
| 66 | +``` |
| 67 | + |
| 68 | +This format represents the standard output from [Curious drawing responses data dictionary](https://mindlogger.atlassian.net/servicedesk/customer/portal/3/article/596082739). |
| 69 | + |
| 70 | +## Feature Extraction Capabilities |
| 71 | + |
| 72 | +The toolkit extracts clinically relevant metrics from digitized drawing data. Currently implemented features include: |
| 73 | + |
| 74 | +- **Temporal Features**: Task completion duration. |
| 75 | +- **Velocity Features**: Velocity analysis including linear, radial, and angular velocity components with statistical measures (sum, median, variation, skewness, kurtosis). |
| 76 | +- **Distance Features**: Spatial accuracy measurements using Hausdorff distance metrics with temporal normalizations and segment-specific analysis. |
| 77 | +- **Drawing Error Features**: Area under the curve (AUC) calculations between drawn paths and ideal reference trajectories to quantify spatial accuracy. |
21 | 78 |
|
22 | 79 | ## Installation |
23 | 80 |
|
24 | | -Install the newest development version via : |
| 81 | +Install the graphomotor package from PyPI: |
| 82 | + |
| 83 | +```sh |
| 84 | +pip install graphomotor |
| 85 | +``` |
| 86 | + |
| 87 | +Or install the latest development version directly from GitHub: |
25 | 88 |
|
26 | 89 | ```sh |
27 | 90 | pip install git+https://github.com/childmindresearch/graphomotor |
28 | 91 | ``` |
29 | 92 |
|
30 | | -## Links or References |
| 93 | +## Quick Start |
| 94 | + |
| 95 | +Currently, `graphomotor` is available as an importable Python library. CLI functionality is planned for future releases. |
| 96 | + |
| 97 | +### Extracting Features from Spiral Drawing Data |
| 98 | + |
| 99 | +```python |
| 100 | +from graphomotor.core import orchestrator |
| 101 | + |
| 102 | +# Path to your spiral drawing data file |
| 103 | +input_file = "path/to/your/spiral_data.csv" |
| 104 | + |
| 105 | +# Directory where extracted features will be saved |
| 106 | +output_dir = "path/to/output/directory" |
| 107 | + |
| 108 | +# Run the analysis pipeline |
| 109 | +features = orchestrator.run_pipeline( |
| 110 | + input_path=input_file, |
| 111 | + output_path=output_dir |
| 112 | +) |
| 113 | + |
| 114 | +# Features are returned as a dictionary and saved as CSV |
| 115 | +print(f"Successfully extracted {len(features)} feature categories") |
| 116 | +``` |
| 117 | + |
| 118 | +For detailed configuration options and additional parameters, refer to the [`run_pipeline` documentation](https://childmindresearch.github.io/graphomotor/graphomotor/core/orchestrator.html#run_pipeline). |
| 119 | + |
| 120 | +> **Note:** Currently, only single file processing is supported, with batch processing planned for future releases. |
| 121 | +
|
| 122 | +## Future Directions |
| 123 | + |
| 124 | +The Graphomotor Study Toolkit is under active development. For more detailed information about upcoming features and development plans, please refer to our [GitHub Issues](https://github.com/childmindresearch/graphomotor/issues) page. |
| 125 | + |
| 126 | +## Contributing |
| 127 | + |
| 128 | +We welcome contributions from the community! If you're interested in contributing, please review our [Contributing Guidelines](CONTRIBUTING.md) for information on how to get started, coding standards, and the pull request process. |
| 129 | + |
| 130 | +## References |
31 | 131 |
|
32 | | -- [A very important resource](https://www.youtube.com/watch?v=dQw4w9WgXcQ) |
| 132 | +1. Messan, K. S., Kia, S. M., Narayan, V. A., Redmond, S. J., Kogan, A., Hussain, M. A., McKhann, G. M. II, & Vahdat, S. (2022). Assessment of Smartphone-Based Spiral Tracing in Multiple Sclerosis Reveals Intra-Individual Reproducibility as a Major Determinant of the Clinical Utility of the Digital Test. Frontiers in Medical Technology, 3, 714682. [https://doi.org/10.3389/fmedt.2021.714682](https://doi.org/10.3389/fmedt.2021.714682) |
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