数据表1:RT-ring——用于基层医疗震颤性帕金森病诊断的小型可穿戴设备

RT-ring可穿戴设备用于震颤性帕金森病诊断的数据表,包含67例患者的惯性特征、肌电图和DaTscan结果。

Rita NisticòRita Nisticò
NIAID Data Ecosystem
浏览 10
表格rest tremortremor patternwearable deviceRT-ringDaTscanParkinson’s diseaseessential tremor plusmachine learning
Data Sheet 1_RT-ring: a small wearable device for tremulous Parkinson’s disease diagnosis in primary care.docx

基本信息

模态
表格
大小
0.000023216 GB
许可
CC BY 4.0
创建/更新时间
2026-10-08
版本
v1

资源简介

数据表1:RT-ring——用于基层医疗震颤性帕金森病诊断的小型可穿戴设备

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 23.22 KB,主题涵盖 rest tremor、tremor pattern、wearable device、RT-ring、DaTscan,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《Data Sheet 1_RT-ring: a small wearable device for tremulous Parkinson’s disease diagnosis in primary care.docx》。配套论文《MDS clinical diagnostic criteria for Parkinson''s disease》发表于 Movement Disorders(2015),DOI:10.1002/mds.26424。源站首次发布:2025-01-27。

【数据内容】

源站原始描述:IntroductionDifferential diagnosis of rest tremor (RT) disorders is challenging, often requiring 123I-ioflupane single-photon-emission-computed tomography (DaTscan), an expensive technique not available worldwide. In the current study, we investigated the performance of a new wearable mobile device termed “RT-ring” in predicting DaTscan result in patients presenting with RT based on rest tremor inertial features. MethodsConsecutive RT patients underwent RT-ring tremor analysis, surface electromy…

中文译文(机器翻译,仅供快速理解,请以原文为准):引言 静止性震颤(RT)疾病的鉴别诊断具有挑战性,通常需要进行123I-ioflupane单光子发射计算机断层扫描(DaTscan),但该技术昂贵且并非全球可及。在本研究中,我们基于静止性震颤的惯性特征,研究了一种称为“RT-ring”的新型可穿戴移动设备在预测表现为RT患者DaTscan结果方面的性能。 方法 连续纳入的RT患者接受了RT-ring震颤分析、表面肌电图(sEMG)和DaTscan检查。RT-ring是一种小型化移动设备,利用基于惯性震颤数据的机器学习来估计RT模式。已证实这种电生理震颤特征能够准确预测DaTscan结果。主要结局是RT-ring区分有和无纹状体多巴胺能缺陷患者的表现。 结果 共纳入67例RT患者,包括42例纹状体多巴胺能缺陷患者和25例DaT

【数据结构与技术规格】

文件数 1 个,合计 23.22 KB。Data Sheet 1_RT-ring: a small wearable device for tremulous Parkinson’s disease diagnosis in primary care.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,23.22 KB。数据集 DOI:10.3389/fneur.2025.1534205.s003。

【主题与分类】

源站学科分类:Neurology and Neuromuscular Diseases。主题标签:rest tremor、tremor pattern、wearable device、RT-ring、DaTscan、Parkinson’s disease、essential tremor plus、machine learning。

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_RT-ring_a_small_wearable_device_for_tremulous_Parkinson_s_disease_diagnosis_in_primary_care_docx/28283456

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Buonocore, Jolanda; Vescio, Basilio; De Maria, Marida; Crasà, Marianna; Nisticò, Rita; Arcuri, Pier P.; et al. (2025). Data Sheet 1_RT-ring: a small wearable device for tremulous Parkinson’s disease diagnosis in primary care.docx. Frontiers. Dataset

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下载信息

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使用方式

数据集获取(Figshare)

命令行下载

curl -L -o "Data Sheet 1_RT-ring: a small wearable device for tremulous Parkinson’s disease diagnosis in primary care.docx" "https://ndownloader.figshare.com/files/51943724"

文件清单

  • Data Sheet 1_RT-ring: a small wearable device for tremulous Parkinson’s disease diagnosis in primary care.docx(23.22 KB)

文件总体积 23.22 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

IntroductionDifferential diagnosis of rest tremor (RT) disorders is challenging, often requiring 123I-ioflupane single-photon-emission-computed tomography (DaTscan), an expensive technique not available worldwide. In the current study, we investigated the performance of a new wearable mobile device termed “RT-ring” in predicting DaTscan result in patients presenting with RT based on rest tremor inertial features.
MethodsConsecutive RT patients underwent RT-ring tremor analysis, surface electromyography (sEMG), and DaTscan. The RT-ring is a miniaturized mobile device that uses machine learning based on inertial tremor data to estimate the RT pattern. This electrophysiologic tremor feature has proven to accurately predict DaTscan result. The primary outcome was the RT-ring’s performance in distinguishing patients with and without striatal dopaminergic deficit.
ResultsSixty-seven RT patients were enrolled, including 42 patients with striatal dopaminergic deficit and 25 with normal DaTscan. The RT-ring showed 85.0% sensitivity, 90.9% specificity, and 87.9% balanced accuracy in predicting DaTscan result, and demonstrated 96.8% agreement with sEMG in RT pattern classification.
ConclusionThe RT-ring is a promising, non-invasive, user-friendly, wearable mobile device for supporting the diagnosis of tremulous Parkinson’s disease in primary care settings, especially in low-income countries with limited access to dopamine imaging.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fneur.2025.1534205.s003(source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_RT-ring_a_small_wearable_device_for_tremulous_Parkinson_s_disease_diagnosis_in_primary_care_docx/28283456)。

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