Measuring time spent outdoors using a wearable camera and GPS

Michael S. Lam, S. Godbole, Jacqueline Chen, M. Oliver, H. Badland, S. Marshall, P. Kelly, C. Foster, A. Doherty, J. Kerr
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引用次数: 17

Abstract

Numerous studies have demonstrated multiple health benefits of being outside and exposure to natural environments. It is essential to accurately measure the amount of time individuals spend outdoors to assess the impact of exposure to outdoor time on health. SenseCam is a wearable camera that automatically captures images. The annotated images provide an objective criterion for determining amount of time spent outdoors. In this paper we explored the use of SenseCam and Global Positioning System (GPS) devices to calculate time spent outdoors. We used the annotated SenseCam images to investigate the optimal threshold from the GPS data to best differentiate outdoor and indoor time. We analyzed the signal strength data recorded by the GPS with a Receiver Operating Characteristic (ROC) curve as well as a three-category logistic regression model. The ROC curve resulted in 79.4% sensitivity for indoor time and 84.1% specificity for outdoor time with an area under the curve of 0.927.
使用可穿戴相机和GPS测量户外活动时间
许多研究表明,户外活动和接触自然环境对健康有多种好处。必须准确测量个人在户外度过的时间,以评估接触户外时间对健康的影响。SenseCam是一款可以自动捕捉图像的可穿戴相机。带注释的图像为确定在户外花费的时间量提供了客观标准。在本文中,我们探索了使用SenseCam和全球定位系统(GPS)设备来计算户外花费的时间。我们使用带注释的SenseCam图像来研究GPS数据的最佳阈值,以最好地区分室外和室内时间。利用接收机工作特征(ROC)曲线和三类logistic回归模型对GPS记录的信号强度数据进行分析。ROC曲线对室内时间的敏感性为79.4%,对室外时间的特异性为84.1%,曲线下面积为0.927。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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