Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001, Covilhã, Portugal.
Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801, Vila Real, Portugal.
Sci Data. 2022 Mar 25;9(1):105. doi: 10.1038/s41597-022-01213-9.
The dataset presented in this paper presents a dataset related to three motionless activities, including driving, watching TV, and sleeping. During these activities, the mobile device may be positioned in different locations, including the pants pockets, in a wristband, over the bedside table, on a table, inside the car, or on other furniture, for the acquisition of accelerometer, magnetometer, gyroscope, GPS, and microphone data. The data was collected by 25 individuals (15 men and 10 women) in different environments in Covilhã and Fundão municipalities (Portugal). The dataset includes the sensors' captures related to a minimum of 2000 captures for each motionless activity, which corresponds to 2.8 h (approximately) for each one. This dataset includes 8.4 h (approximately) of captures for further analysis with data processing techniques, and machine learning methods. It will be useful for the complementary creation of a robust method for the identification of these type of activities.
本文介绍了一个与三种静态活动相关的数据集，包括驾驶、看电视和睡觉。在这些活动中，移动设备可能位于不同的位置，包括裤袋、手腕带、床头柜上、桌子上、车内或其他家具上，以获取加速度计、磁力计、陀螺仪、GPS 和麦克风数据。该数据由 25 名个体（15 名男性和 10 名女性）在葡萄牙的 Covilhã 和 Fundão 市的不同环境中收集。该数据集包括与每个静态活动相关的最小 2000 次捕获的传感器捕获，每个活动对应约 2.8 小时（大约）。该数据集包含约 8.4 小时的捕获，可进一步使用数据处理技术和机器学习方法进行分析。它将有助于为这些类型的活动的识别创建稳健的方法。
