ThermalCOVID19
收藏DataCite Commons2021-05-28 更新2024-07-28 收录
下载链接:
https://figshare.com/articles/dataset/ThermalCOVID19/13296887/2
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资源简介:
Standardized Thermal videos and meta data of people going to be tested for COVID-19<br><b>Termal_IRS.7z.001 to Termal_IRS.7z.011</b>:Raw Thermal Files in 7z Format<b>ThermalData.zip:</b>mp4 videos, avi standardized videos, and Matlab scripts<b><br></b><b>FinalThermalMetaDataV2.xlsx:</b>Patient Evaluation: PCR, Demographics Vital Signs, Symptoms <br>jpg_BackgroundFiles.zipPhotos of back wall as reference<br>DebluringVideoGeneration.m<br>Matlab script for AVI file generation<br><br>Abstract:The prospective upper body thermal images SARS-CoV2 association study was designed to test the hypothesis that thermal videos may aid in the early diagnosis of COVID-19. The study recorded a set of measurements from 252 participants regarding PCR-results, demographics, vital signs, participant activities, medications, respiratory symptoms, and a thermal video session where the volunteers performed simple breath-hold in four different positions. The acquired data may be used to test clinical association’s questions regarding temperature patterns, demographics, and vital signs. Furthermore, it could be valuable to develop new computer algorithms for extracting useful scientific information from thermal videos. The data is open access and free to use for any research purpose. <br>
用于新冠病毒检测人群的标准化热成像视频与元数据<br><b>Termal_IRS.7z.001 至 Termal_IRS.7z.011</b>:7z 格式原始热成像文件<br><b>ThermalData.zip</b>:包含 MP4 视频、AVI 标准化视频及 Matlab 脚本<br><b>FinalThermalMetaDataV2.xlsx</b>:受试者评估信息,涵盖核酸检测(聚合酶链式反应,PCR)结果、人口统计学特征、生命体征与症状<br>jpg_BackgroundFiles.zip:作为参考背景的后壁照片<br>DebluringVideoGeneration.m:视频去模糊生成的 Matlab 脚本<br>Matlab script for AVI file generation:用于 AVI 文件生成的 Matlab 脚本<br><br>摘要:本前瞻性上肢热成像图像与严重急性呼吸综合征冠状病毒2(SARS-CoV-2)关联研究旨在验证"热成像视频可辅助新冠病毒早期诊断"这一科学假说。研究共纳入252名受试者,采集其核酸检测(PCR)结果、人口统计学信息、生命体征、活动情况、用药史、呼吸道症状等多维度数据,并记录了受试者在四种不同体位下完成简单屏气动作的热成像视频片段。所获数据集可用于验证与体温模式、人口统计学特征及生命体征相关的临床关联问题,同时可为开发从热成像视频中提取有效科学信息的新型计算机算法提供重要支撑。本数据集为开源开放资源,可免费用于各类科研用途。
提供机构:
figshare
创建时间:
2021-02-04



