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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >A Physical Activity Reference Data-Set Recorded from Older Adults Using Body-Worn Inertial Sensors and Video Technology—The ADAPT Study Data-Set
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A Physical Activity Reference Data-Set Recorded from Older Adults Using Body-Worn Inertial Sensors and Video Technology—The ADAPT Study Data-Set

机译：使用身体惯性传感器和视频技术从老年人记录的体育锻炼参考数据集— ADAPT研究数据集

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Physical activity monitoring algorithms are often developed using conditions that do not represent real-life activities, not developed using the target population, or not labelled to a high enough resolution to capture the true detail of human movement. We have designed a semi-structured supervised laboratory-based activity protocol and an unsupervised free-living activity protocol and recorded 20 older adults performing both protocols while wearing up to 12 body-worn sensors. Subjects’ movements were recorded using synchronised cameras (≥25 fps), both deployed in a laboratory environment to capture the in-lab portion of the protocol and a body-worn camera for out-of-lab activities. Video labelling of the subjects’ movements was performed by five raters using 11 different category labels. The overall level of agreement was high (percentage of agreement >90.05%, and Cohen’s Kappa, corrected kappa, Krippendorff’s alpha and Fleiss’ kappa >0.86). A total of 43.92 h of activities were recorded, including 9.52 h of in-lab and 34.41 h of out-of-lab activities. A total of 88.37% and 152.01% of planned transitions were recorded during the in-lab and out-of-lab scenarios, respectively. This study has produced the most detailed dataset to date of inertial sensor data, synchronised with high frame-rate (≥25 fps) video labelled data recorded in a free-living environment from older adults living independently. This dataset is suitable for validation of existing activity classification systems and development of new activity classification algorithms.
机译：身体活动监测算法通常是在不代表现实生活活动的条件下开发的，没有使用目标人群开发的，或者未标记为足够高的分辨率以捕获人类运动的真实细节的条件。我们设计了半结构的基于实验室的监督活动协议和无监督的自由活动协议，并记录了20位老年人在同时佩戴多达12个穿戴传感器的情况下执行这两种协议。使用同步摄像机（≥25fps）记录对象的运动，这两个摄像机都部署在实验室环境中以捕获协议的实验室内部分，还配备了用于实验室外活动的随身摄像机。五个评分者使用11种不同的类别标签对对象的运动进行视频标记。总体协议水平很高（协议百分比> 90.05％，科恩的Kappa，校正后的Kappa，Krippendorff的alpha和Fleiss的Kappa> 0.86）。总共记录了43.92小时的活动，其中包括9.52小时的实验室内活动和34.41小时的实验室外活动。在实验室内和实验室外场景中，分别记录了计划转换的88.37％和152.01％。这项研究产生了迄今为止最详细的惯性传感器数据集，并与在独立生活的老年人中自由生活的环境中记录的高帧频（≥25 fps）视频标记数据同步。该数据集适用于验证现有活动分类系统和开发新的活动分类算法。

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