Home-based measurements of dystonia and choreoathetosis in cerebral palsy using smartphone-coupled inertial sensor technology and machine learning: A proof-of-concept study - dataset

Home-based measurements of dystonia in cerebral palsy using smartphone-coupled inertial sensor technology and machine learning: A proof-of-concept study This project contains: - 1 main MATLAB script: MODYSathome_main.m<br> - 12 MATLAB functions:<br> - function_calc_mean_recall_precision.m<br> - function_create_dataframes.m<br> - function_deep_learning.m<br> - function_determine_best_ML_model.m<br> - function_display_DL_results.m<br> - function_display_ML_results.m<br> - function_index_extremities.m<br> - function_machine_learning.m<br> - function_oversample.m<br> - function_partition_data.m<br> - function_pick_best_models.m<br> - function_prepare_DL_data.m Downloading the Matlab scripts - Create a folder named 'MODYS' and create a subfolder named 'results'<br> - Download the zip file via RehabAUmc/modys-at-home: v1.0 | Zenodo<br> - Unzip the zip file in the path MODYS\ STEPS<br> 1. Open MATLAB<br> 2. In MATLAB, go to the 'HOME' tab and click on 'Set Path'<br> 3. Click on 'Add Folder' and browse to MODYS/RehabAUmc-modys-at-home-86b14c3/functions<br> 4. Click on 'Select Folder' and click on 'Save'<br> 5. Click on 'Browse to folder' and browse to a patients' data in MODYS/data/PatientXXX, then click on 'Select Folder'<br> 6. In the 'HOME' tab click on 'Open' and open MODYSathome.m in MODYS/RehabAUmc-modys-at-home-86b14c3<br> 7. In the 'EDITOR' tab click on 'Run Section' to run the script<br> 8. When the code has been run, the results are displayed in the Command Window and saved in MODYS/results/PatientXXX基于智能手机耦合惯性传感器技术与机器学习的脑瘫肌张力障碍居家测量：一项概念验证研究 本项目包含以下内容： - 1个主MATLAB脚本：MODYSathome_main.m - 12个MATLAB函数： - function_calc_mean_recall_precision.m - function_create_dataframes.m - function_deep_learning.m - function_determine_best_ML_model.m - function_display_DL_results.m - function_display_ML_results.m - function_index_extremities.m - function_machine_learning.m - function_oversample.m - function_partition_data.m - function_pick_best_models.m - function_prepare_DL_data.m ### MATLAB脚本下载与配置 - 创建名为MODYS的文件夹，并在其中新建名为results的子文件夹 - 通过RehabAUmc/modys-at-home: v1.0 | Zenodo 下载压缩包 - 将压缩包解压至路径 MODYSSTEPS 下 ### 运行流程 1. 打开MATLAB 2. 在MATLAB的「主页」选项卡中点击「设置路径」 3. 点击「添加文件夹」，浏览至 MODYS/RehabAUmc-modys-at-home-86b14c3/functions 路径 4. 点击「选择文件夹」，随后点击「保存」 5. 点击「浏览至文件夹」，选择 MODYS/data/PatientXXX 下的患者数据文件夹，点击「选择文件夹」 6. 在「主页」选项卡中点击「打开」，打开 MODYS/RehabAUmc-modys-at-home-86b14c3 中的 MODYSathome.m 脚本 7. 在「编辑器」选项卡中点击「运行节」以运行该脚本 8. 代码运行完成后，结果将显示在命令行窗口中，并保存至 MODYS/results/PatientXXX 路径下