表1：识别运动障碍新表型特征的智能设备系统

数据集获取（Figshare）

• 源站标题：Table_1_A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders.DOCX
• DOI：10.3389/fneur.2019.00048.s001
• 发布日期：2019-01-30
• 文件数：1 个
• 文件总体积：675.97 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_1_A_Smart_Device_System_to_Identify_New_Phenotypical_Characteristics_in_Movement_Disorders_DOCX/7647749

命令行下载

curl -L -o "Table_1_A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders.DOCX" "https://ndownloader.figshare.com/files/14207555"

文件清单

• Table_1_A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders.DOCX（675.97 KB）

文件总体积 675.97 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

Parkinson’‘s disease and Essential Tremor are two of the most common movement disorders and are still associated with high rates of misdiagnosis. Collected data by technology-based objective measures (TOMs) has the potential to provide new promising and highly accurate movement data for a better understanding of phenotypical characteristics and diagnostic support. A technology-based system called Smart Device System (SDS) is going to be implemented for multi-modal high-resolution acceleration measurement of patients with PD or ET within a clinical setting. The 2-year prospective observational study is conducted to identify new phenotypical biomarkers and train an Artificial Intelligence System. The SDS is going to be integrated and tested within a 20-min assessment including smartphone-based questionnaires, two smartwatches at both wrists and tablet-based Archimedean spirals drawing for deeper tremor-analyses. The electronic questionnaires will cover data on medication, family history and non-motor symptoms. In this paper, we describe the steps for this novel technology-utilizing examination, the principal steps for data analyses and the targeted performances of the system. Future work considers integration with Deep Brain Stimulation, dissemination into further sites and patient’'s home setting as well as integration with further data sources as neuroimaging and biobanks. Study Registration ID on ClinicalTrials.gov: NCT03638479.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fneur.2019.00048.s001（source: https://frontiersin.figshare.com/articles/dataset/Table_1_A_Smart_Device_System_to_Identify_New_Phenotypical_Characteristics_in_Movement_Disorders_DOCX/7647749）。